Systems and methods for generating an enhanced error message are provided. An example method includes: receiving one or more raw error messages. The one or more raw error messages include one or more stack traces. The method further includes matching at least one raw error message of the one or more raw error messages to one or more error rules from a plurality of error rules. The one or more error rules include regular expression patterns. The method further includes parsing the at least one raw error message, based on the one or more matched error rules from the plurality of error rules; and generating one or more enhanced error messages, based on the at least one parsed raw error messages. The one or more enhanced error messages include one or more natural language sentences. The method further includes embedding the one or more enhanced error messages into a website.
A method comprising maintaining a configuration definition associated with a local repository, the configuration definition having markup code in a markup language, symbolically specifying instructions, parameters, settings, or configurations of users, groups, or permissions relating to access to artifacts stored in a plurality of repositories distributed across multiple regional clusters, each regional cluster being a grouping of one or more repositories serving a particular geographic region, the plurality of repositories including a replicated mirror of an external repository outside the multiple regional clusters; detecting a change to the configuration definition; transforming, in response to the detecting, the markup code in the configuration definition into specific commands or parameter values that need to be written into each repository on a regional cluster, comprising deriving settings including a topology of permissions for the regional cluster and a strategy of mirroring the regional cluster to another regional cluster; deploying the specific commands or parameter values on the regional cluster.
H04L 41/0816 - Configuration setting characterised by the conditions triggering a change of settings the condition being an adaptation, e.g. in response to network events
G06F 3/06 - Digital input from, or digital output to, record carriers
G06F 8/71 - Version control ; Configuration management
G06F 16/17 - File systems; File servers - Details of further file system functions
Systems and methods for converting a raster image with a corresponding color scale into a plurality of vectors are provided. An example method includes receiving the raster image and the color scale. In some embodiments, the color scale includes a plurality of colors and a plurality of unit values. In certain embodiments, each color of the plurality of colors corresponds to a unit value of the plurality of unit values. In some embodiments, the raster image includes a plurality of pixels each corresponding to a pixel color. In certain embodiments, each color of the plurality of colors is segmented into a plurality of color channel values. In some embodiments, a model is trained to convert a color to a vector value based on the plurality of segmented color channel values for each color of the plurality of colors and the plurality of unit values. In certain embodiments, the plurality of vectors are generated and each include a vector location, a geometric shape, and a vector value.
Methods and systems for structuring, storing and displaying time series data in a user interface. One system includes processors executing instructions to determine, from time series data from a first sensor, a first subset of time series data for the first batch from the first start time and the first end time, determine, from the time series data from the first sensor, a second subset of time series data for the second batch from the second start time and the second end time, generate a time series user interface comprising a chart, the chart including a first plot for the first subset of time series data and a second plot for the second subset of time series data, the first plot being aligned to the second plot, and cause presentation of the time series user interface.
G06F 11/32 - Monitoring with visual indication of the functioning of the machine
G06F 16/36 - Creation of semantic tools, e.g. ontology or thesauri
G06F 16/383 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
A method, performed by one or more processors, including: receiving one or more event records; generating, using the one or more event records, an event descriptor object descriptive of one or more events occurring in a networked system, wherein the event descriptor object comprises a plurality of event properties; receiving one or more entity records; generating, using the one or more entity records, an entity descriptor object descriptive of one or more entities relevant to the security of the networked system, wherein the entity descriptor object comprises a plurality of entity properties; incorporating, into an object graph, the event descriptor object and the entity descriptor object; and associating, in the object graph, the event descriptor object with the entity descriptor object using at least one of the plurality of event properties and at least one of the plurality of entity properties.
Computer-implemented systems and methods are disclosed to interface with a storage device storing a file, wherein the file comprises first data associated with an artifact configured to be displayed in a first interface at a first electronic device, the artifact including a first representation state representing a first visual depiction of one or more data objects. In accordance with some embodiments, a method is provided to provide access via the first interface to the one or more data objects. The method comprises acquiring the first data associated with artifact. The method further comprises acquiring an activation of at least part of the artifact, and responsive to acquiring the activation, transmitting a first request to a second electronic device for second data associated with the artifact. The method further comprises acquiring the second data, wherein the second data allows the first visual depiction to be altered to a second visual depiction.
A computing system accesses one or more code lists, each including a plurality of items, each item comprising an alphanumerical machine code mapped to a human recognizable concept. The system may receive a query from a user, determine any matching and/or related items in the code lists, and generate an interactive visualization of the matching items. The visualization allows the user to view and detect relationships between items from multiple code lists in a manner that is not possible through review of the lists separately. The user can select nodes in a tree structured visualization to initiate addition of the corresponding alphanumerical machine codes to a custom code list.
Systems and methods are provided for investigation network activities. Network activity information may be accessed. The network activity information may describe for an individual (1) respective relationship with one or more persons; and (2) respective activity status information indicating whether a given person has engaged in a particular activity. A network activity graph may be generated based on the network activity information. The network activity graph may include two or more nodes representing the individual and the one or more persons. Connections between the nodes may represent the respective relationships between the individual and the one or more persons. Data corresponding to the network activity graph may be presented through an interface.
System and method for control area visualization according to certain embodiments. For example, a method includes: receiving object data from a plurality of data sources; identifying a plurality of first objects associated with a first group based at least in part on the object data, each first object of the plurality of first objects being associated with a geospatial location and a buffer area; determining a first control area associated with the first group based at least in part on the geospatial location and the buffer area of each first object of the plurality of first objects; and causing a presentation of the first control area on a display.
A method comprises storing first transaction data for a first transaction producing a first version of a first dataset, second transaction data for a second transaction transforming a first version of the first dataset to a second version of the first dataset, and third transaction data for a third transaction transforming the second version of the first dataset to a third version of the first dataset; storing dependency information indicating a first dependency of the third transaction on the second transaction and a second dependency of the second transaction on the first transaction; receiving a first instruction to revoke a first permission of a first user to access the second version of the first dataset; automatically revoking a certain permission of the first user to access the third version of the first dataset based on the dependency information.
A method includes receiving an indication of a request from a client device. The request is for establishing an access session to perform one or more actions on data of a data processing platform. The method includes receiving data indicative of a context of the access session request and establishing a challenge session associated with the request that indicates one or more challenges required of a user associated with a client device to successfully respond to in order to establish the requested access session, a number or a type of the one or more challenges being determined based on the context, and establishing an access session to enable the user to perform the one or more actions on the data of the data processing platform if responses to all challenges in the challenge session are successful.
H04L 9/32 - Arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system
A computer-implemented method is disclosed. The method comprises managing, by a processor, a connected entity graph of nodes and edges, each node of the nodes representing an entity having an entity type of a plurality of entity types, at least one node of the nodes having an entity type of an electronic note, each edge of the edges representing a relationship between two entities; receiving a request for a search specifying a beginning entity, a linking parameter, and a filter on the linking parameter, the linking parameter specifying a property of an intermediary entity linking a source entity and a target entity during the search, the filter constraining a value of the property; searching the connected entity graph based on the request; causing a display of a search result.
A method comprises receiving a query via a graphical user interface (GUI); running the query against a gazetteer system to obtain one or more geographical coordinates; causing a presentation in the GUI of a digital map including a set of regions corresponding to a set of geographical coordinates from the one or more geographical coordinates; receiving a selection of a region of the set of regions; causing a presentation in the GUI a geotag dialog for an object corresponding to the region, the object being of an object type in an ontology model and having a plurality of properties; receiving via the geotag dialog a selection of a property of the plurality of properties; associating a geotag with the property, the geotag including a geographical coordinate of the one or more geographical coordinates corresponding to the region, wherein the method is performed by one or more processors.
Systems and methods are provided for storing a first data object comprising a first set of immutable components, the first data object being associated with a corresponding second data object stored by a remote replication system. A difference is determined between the first set of immutable components of the first data object and a second set of immutable components of the corresponding second data object. A subset of immutable components is identified from the first set of immutable components based on the difference. The subset of immutable components from the first set of immutable components is provided to the remote replication system over a communication network.
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
A computing system and methods are provided for georeferencing stabilization. An exemplary method includes: obtaining a video stream capturing an area from a camera of a drone, where the video stream includes a plurality of frames, each including a field of view of the image capturing device and metadata of the image capturing device when the frame is captured; constructing a geographic (geo) lattice for the field of view in each of the plurality of frames, the geo lattice comprises a plurality of points, each being associated with raw coordinates determined based on the corresponding metadata; and building a lattice map with stabilized geo coordinates by (1) aligning the frames, (2) averaging the raw geo coordinates for given intersection points, and (3) building the lattice map based on the averaged geo coordinates of the intersection points.
Example embodiments involve a metrics collection system for collecting software usage metrics from one or more client devices at deployments. A computer, such as a server configured to execute the metrics collection system, collects software usage metrics (e.g., as a metrics submission from a client device) of the software product at the deployment, identifies a metrics type of the software usage metrics collected, assigns the software usage metrics to a metrics category, and calculates and updates a metrics score of the metrics category, based on the software usage metrics collected.
A method comprises receiving, at a build service of a build server, an external dataset and an adaptor application module, the external dataset being in a specific format, the adaptor application module providing information relevant to a build pipeline maintained by the build service for building an output dataset based on the external dataset, the information including changes to the external dataset since a previous build of the output dataset is performed and a data schema used in the previous build, the build pipeline involving data only in one or more formats other than the specific format; incorporating the external dataset into the build pipeline without the external dataset being reformatted in accordance with requirements of the build service; receiving a request from the adaptor application module for specific information relating to a most recent data build run by the build service; providing a response to the adaptor application module.
In some embodiments, a method comprises obtaining a video stream of a portion of a geographic area, the video stream comprising a plurality of video frames, each of the plurality of video frames captured at a respective first time. Contextual metadata is obtained, the contextual metadata associated with one or more objects located in the portion of the geographic area at a second time, the second time being before each of the respective first times. The contextual metadata is inserted into one or more of the plurality of video frames, thereby causing the contextual metadata associated with the one or more objects to be overlaid on one or more corresponding portions of the one or more of the plurality of video frames.
A computer-implemented method comprises creating and storing a plurality of different access group identifiers each associated with one or more user account identifiers, and a plurality of different classification markings each representing a different access restriction for an electronic document, and associating each of the user account identifiers with one or more of the classification markings; indexing each particular electronic document among a plurality of different electronic documents in association with values of one or more of the access group identifiers and with an inverse list of values of the classification markings that apply to the particular electronic document in a classification index; receiving a search query that specifies one or more attributes of electronic documents; obtaining one or more first classification markings, among the plurality of classification markings, which are associated with a particular user account identifier that is associated with the search query; executing a search of the classification index based on the search query using a covering query that requires a specified minimum number of matches between the one or more first classification markings and one or more second classification markings that are associated with a particular electronic document, and adding the particular electronic document to a result set of the search only when the covering query is satisfied; providing the result set in response to the search query.
Systems and methods are provided for tracking and enforcing relationships between items. A relationship interface may be provided that conveys the relationship (or link) between items, and through which a user may define the link between two or more items. Identifying a link between two items may establish a set of one or more rules to be enforced with respect to the use of one or both of the items (e.g., when the items are stored, when the items are used to create other items, when other items are associated with the items). In various embodiments, violations of one or more rules may be identified and provided via the user interface. In some embodiments, new items that conflict with one or more rules may be prevented from being committed.
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
21.
PIPELINE TASK VERIFICATION FOR A DATA PROCESSING PLATFORM
A pipeline task verification method and system is disclosed, and may use one or more processors. The method may comprise providing a data processing pipeline specification, wherein the data processing pipeline specification defines a plurality of data elements of a data processing pipeline. The method may further comprise identifying from the data processing pipeline specification one or more tasks defining a relationship between a first data element and a second data element. The method may further comprise receiving for a given task one or more data processing elements intended to receive the first data element and to produce the second data element. The method may further comprise verifying that the received one or more data processing elements receive the first data element and produce the second data element according to the defined relationship.
Disclosed herein are systems and methods for generating notional data. The method includes: receiving seed data of one or more object types in a base dataframe; defining one or more functional relationships associated with the one or more object types, at least one functional relationship of the one or more functional relationships specifying a change to seed data of one object type of the one or more object types; generating data of the one or more object types based at least in part on the seed data in the base dataframe and the one or more functional relationships; and generating the notional data based at least in part on the generated data of the one or more object types.
A method comprises creating metadata identifying columns of tables and column operations of one or more data transforms of the columns in a data pipeline and including links to code segments in human-readable form corresponding to the one or more data transforms; executing a build job that effects the one or more data transforms on one or more datasets to generate one or more derived datasets; causing, after the executing, a presentation of a graphical user interface (GUI) including a graphical representation of the one or more data transforms based on the metadata, wherein the method is performed by one or more processors.
G06F 16/26 - Visual data mining; Browsing structured data
G06F 16/21 - Design, administration or maintenance of databases
G06F 16/22 - Indexing; Data structures therefor; Storage structures
G06F 16/25 - Integrating or interfacing systems involving database management systems
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
Systems and methods for dynamically generating application programming interfaces and managing functions associated with a data object type. In an aspect, the system accesses an object definition for a type of data object. The system generates an application programming interface associated with the type of data object, based at least partly on the object definition. The system determines a change to the object definition for the type of data object and updates the application programming interface based at least partly on the change to the object definition.
Systems and methods are provided for master-to-master OT-based artifact peering. A “master-to-master” architecture for artifacts is implemented in a network comprising a plurality of nodes and clients, where no node is designated a “master” or “primary” for a given artifact. A first node receives a subset of remote proposed operations from a second node and determines if a conflict exists between the received subset of remote proposed operations and at least one of a plurality of locally-proposed operations. The first node resolves the conflict based on a total-ordering agreed upon between the first node and the second node. The first node transforms at least one operation, either received or locally-proposed, based on the resolved conflict. The first node than updates a local log to include the transformed operation.
An error management system can provide search results based on a received stack trace. For example, the error management system receives, from a client device, a search query including a stack trace. The error management system parses the search query to identify at least a first class and one or more errors associated with the first class, yielding a parsed search query. The error management system searches a class mapping table based on the parsed search query. The class mapping table includes a listing of classes and corresponding links to source code. The error management system searches an error discussion database based on the parsed search query. The error discussion database includes one or more user generated postings regarding programming errors. The error management system provides, to the client device, search results resulting from searching the class mapping table and the error discussion database.
SYSTEMS AND METHODS FOR GENERATING AND DISPLAYING A DATA PIPELINE USING A NATURAL LANGUAGE QUERY, AND DESCRIBING A DATA PIPELINE USING NATURAL LANGUAGE
System and method for generating and displaying data pipelines according to certain embodiments. For example, a method includes: receiving a natural language (NL) query; receiving a model result generated based on the NL query, the model result including a query in a standard query language, the model result being generated using one or more computing models; and generating the data pipeline based at least in part on the query in the standard query language, the data pipeline comprising one or more data pipeline elements, at least one data pipeline element of the one or more pipeline elements being corresponding to a query component of the query in the standard query language.
System and method for solution proposal workflow according to certain embodiments. For example, a method includes: generating an alert, the alert associated with one or more objects; identifying one or more possible solutions associated with the alert, the one or more possible solutions including one or more actions applicable to the one or more objects; applying a filter to the one or more possible solutions to select one or more solutions from the one or more possible solutions; and presenting the one or more selected solutions.
System and method for processing time-related geospatial data from one or more data sources. For example, a system includes an application server; and a storage. The application server is configured to: receive data including temporal information and geospatial information for each data object of one or more data objects, send the data to a client device to display the data on a map, and generate one or more first multi-dimensional tiles based at least in part on the temporal information and the geospatial information. The one or more first multi-dimensional tiles correspond to a temporal dimension associated with a first temporal width. The application server is further configured to send the one or more first multi-dimensional tiles to store in the storage for retrieval by the client device.
Systems and methods for video georegistration are provided. An example method includes: receiving an input image; generating a plurality of templates from the input image; and generating a template queue based at least in part on the plurality of template scores. The plurality of templates are associated with a plurality of template scores. The template queue includes a set of selected templates. The method further includes receiving one or more reference images; determining a set of match scores for the set of selected templates by applying a matching algorithm to the set of selected templates and at least one reference image of the one or more reference images; evaluating the set of match scores to select a collection of templates, and generating an image transform based at least in part on the collection of templates. Each template of the collection of templates meets one or more selection criteria.
Systems and methods generate a first security node hash identifier by performing a first hash operation, such as a one-way hash, on a first data resource identifier associated with a first data resource, such as a data set, produced by a data resource platform. The systems and methods generate a dependent second security node hash identifier by performing a second hash operation on a second data resource identifier associated with a dependent second data resource produced by the data resource platform and on the first security node hash identifier, receive an access request for access to the dependent second data resource; and in response to the access request, grant permission to access the dependent second data resource to a user associated with the access request based on the dependent second security node hash identifier.
H04L 9/06 - Arrangements for secret or secure communications; Network security protocols the encryption apparatus using shift registers or memories for blockwise coding, e.g. D.E.S. systems
H04L 41/22 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks comprising specially adapted graphical user interfaces [GUI]
Systems, computer program products, and computer-implemented methods for determining relationships between one or more outputs of a first model and one or more inputs of a second model that collectively represent a real world system, and chaining the models together. For example, the system described herein may determine how to chain a plurality of models by training an artificial intelligence system using the nodes of the models such that the trained artificial intelligence system predicts related output and input node connections. The system may then link related nodes to chain the models together. The systems, computer program products, and computer-implemented methods may thus, according to various embodiments, enable a plurality of discrete models to be optimally chained.
A method of enabling propagated deletion in a distributed database system is disclosed. The method comprises receiving a request to delete data in a distributed database system; causing a display of a relevant dataset and a switch between applying propagated deletion or not; receiving a first selection of a subset of records from the relevant dataset using one or more filter functions and a second selection of applying propagated deletion to the subset of records; and applying propagated deletion to the subset of records to generate a new dataset.
Systems and methods are provided for enhanced processing of time series data via parallelization of instructions. An example method includes receiving a query indicating time series datasets and operations to be performed on the time series datasets. Nodes associated with the query are identified, with each node associated with a time series dataset. Nodes associated with operations to be performed are generated. The nodes are assembled into query tree, with parent nodes of the query tree indicating operations that are to be applied to children nodes. Instructions for processing the query tree are generated. At least a subset of the instructions is provided to one or more compute systems for processing in parallel. Results are received, and presented in a user interface.
A method is provided for determining angular relationships from a point of interest to a plurality of peripheral points of interest on a map. One or more cost functions from the point of interest to the plurality of the peripheral points of interest on the map are analyzed. A plurality of vectors emanating from the point of interest to the plurality of the peripheral points of interest on a different representation of the map are displayed. Another method is provided for identifying points of interest on a map. Regions of high interest are identified on the map. Regions of low interest are identified on the map. The regions of high interest are expanded on a different representation of the map. The regions of low interest are contracted by an amount proportional to an amount the regions of high interest are expanded on the different representation of the map.
Computing systems, methods, and non-transitory storage media are provided for determining raw data and additional information from a first storage space to be backed up, obtaining a first snapshot of the raw data and the additional information at a first time, determining one or more parameters of the backing up process based on current or historical network conditions, generate, according to the one or more parameters, a first backup corresponding to the first snapshot at a second storage space, obtaining a second snapshot of the raw data and the additional information at a second time; and generating an incremental backup corresponding to the second snapshot at the second storage space.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 11/07 - Responding to the occurrence of a fault, e.g. fault tolerance
An incentive management system can receive one or more data items associated with a member of an organization; categorize said one or more data items; and store, according to the categorization, the one or more data items in at least one of a plurality of data sets. The system can access the plurality of data sets to retrieve relevant data to automatically calculate an incentive based at least in part on the retrieved data.
A method performed by one or more processors comprises displaying code, receiving user selection of a portion of code, determining one or more settable data items, generating a template, displaying the template, receiving a user input value for the settable data items by the template, and executing the code with each of the settable data items set to the received user input value. A data processing pipeline is configured to pass a data item to a first transformer to provide first transformed data, store the first transformed data in a temporary memory, write the first transformed data to the data storage system, and pass the transformed data from the temporary memory to a second transformer.
Systems and methods for image scoring are disclosed. For example, the method includes: receiving a plurality of images, each image of the plurality of images associated with a geographic metadata, the plurality of images associated with one or more geographic metadata; selecting a first set of images from the plurality of images, each image in the first set of images being associated with a first geographic metadata that is one of the one or more geographic metadata; obtaining one or more first labels indicating one or more object classes respectively for each image in the first set of images; and determining one or more first scores for the one or more object classes for the first geographic metadata based at least in part on the one or more first labels.
G06V 20/70 - Labelling scene content, e.g. deriving syntactic or semantic representations
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
Systems and methods for identifying associations between a code snippet query and stored computer code stored. The method can receive a code query identifying a code snippet to search for, determine a fingerprint of the query code snippet, and search the stored software using the fingerprint to identify software results of code similar to the query code snippet. The fingerprint can be determined by generating k-grams of the code snippet. The k-grams used for the search can be down-selected based on a winnowing process. The method can remove from the software results code that is associated with sanctioned software. The method can include coalescing the software results to produce a subset of the software results, generating a code search user interface comprising information indicative of the subset of software results, and causing presentation of the code search user interface and displaying the subset of software results.
Disclosed herein is a data structure which includes a sequence of events, each event associated with a sequence number indicating a temporal position of an event within the sequence of events; one or more read-offsets, each read-offset associated with a consumer, wherein each read-offset indicates a sequence number up to which a consumer has read events within the sequence of events; and at least one snapshot which represents events with sequence numbers smaller than the smallest read-offset in a compacted form. Disclosed herein is also a computer-implemented method of maintaining the data structure. Disclosed herein is a computer-implemented method, wherein the method is performed on a sequence of events accessible by a plurality of consumers, each event associated with a sequence number indicating a temporal position of an event within the sequence of events, each consumer associated with a read-offset indicating the sequence number up to which the consumer has read events within the sequence of events, the method includes determining a smallest read-offset of all read-offsets; compacting events with sequence numbers smaller than the smallest read-offset into a snapshot; and replacing the events with sequence numbers smaller than the smallest read-offset with the snapshot. Disclosed herein are corresponding computer-readable media and computing systems.
Systems and methods for lineage-aware data retention are provided. An example method includes receiving information of a committed transaction. The committed transaction is configured to add or change data to a dataset. The example method further includes receiving one or more lineages for the committed transaction, determining one or more parent transactions based at least in part on the one or more lineages, obtaining one or more parent retention dates that correspond to the one or more parent transactions respectively, and determining a transaction retention date for the committed transaction based at least in part on the one or more parent retention dates.
A method of cohorting data sets can include accessing a plurality of data sets each associated with a different target item and a plurality of test items and receiving from a user a selection of a plurality of the data sets. For each of the selected data sets, the method may include determining one or more of the test items interacting with the respective target within a threshold parameter and identifying one or more matching test items of the plurality of test items associated with interactions with each of the targets of the selected data sets. The method can include generating a graphical user interface to display a representation of the matching test items, the selected data sets, or both and receiving a filter selection for reducing a number of the matching test items to a filtered one or more test items smaller than the number of matching test items.
An apparatus, and a method, performed by one or more processors are disclosed. The method receives a build request associated with performing an external data processing task on a first data set, the first data set being stored in memory associated with a data processing platform to be performed at a system external to the data processing platform. The method generates a task identifier for the data processing task, and provides, in association with the task identifier, the first data set to an agent associated with the external system with an indication of the data processing task, the agent being arranged to cause performance of the task at the external system, to receive a second data set resulting from performance of the task, and to provide the second data set and associated metadata indicative of the transformation. The method receives the second data set and metadata from the agent associated with the external system and stores the second data set and associated metadata.
Computing systems methods, and non-transitory storage media are provided for receiving a monitoring request. The monitoring request includes one or more entities or attributes to be monitored, one or more rules to be evaluated with respect to the entities or attributes, and one or more downstream actions to be selectively triggered based on the evaluation. Next, data regarding the entities or the attributes is obtained. Next, a log is generated. The log includes changes or updates, relative to a previous iteration, of the entities or the attributes. The changes or updates correspond to the rules. Next, the changes or the updates are evaluated against the one or more rules and based on the log. Next, one or more actions are selectively implemented based on the evaluation of the changes or the updates.
Aspects of the present disclosure relate to computer system security. A machine accesses a set of records corresponding to a set of users having access to a computer system. The machine stores, for each user in the set of users, a baseline profile representing baseline activity of the user with respect to a set of data sources of the computer system. The machine monitors activity of the set of users with respect to the set of data sources. The machine determines, based on monitoring the activity of the set of users, that a user action of a specified user, with respect to one or more data sources from the set of data sources, is anomalous relative to the baseline profile of the specified user. The machine provides a digital transmission representing the anomalous user action.
Systems and methods are provided for coordinating the deployment of frontend assets to defined user groups. Individual groups of users may be assigned to a track comprising a set of frontend assets. Each set of frontend assets may comprise each of the individual components required to generate an entire frontend for an application. In some embodiments, different versions of a single component may be assigned within different tracks. As such, one set of users may be provided a first version of an application and a second set of users may be provided a second version of that application. By associating a new or updated version of a component to a given track, a new or updated version of a component not yet ready for widespread deployment may be provided to only a limited number of users.
Systems, methods, and non-transitory computer-readable media can be configured to perform receiving a notification of a maintenance event associated with a resource. The method includes retrieving historic maintenance data in relation to the resource with which the fault is associated, the maintenance information originating from a time period preceding the time of the maintenance event. The method includes identifying at least a portion of the retrieved historic maintenance data as being indicative of the maintenance event. The method also includes causing the portion of the retrieved historic maintenance data identified as being indicative of the maintenance event to be stored as a precursor signal of the maintenance event. The method also includes causing future maintenance data received from a plurality of resources related to the resource with which the maintenance event is associated to be monitored to predict a future occurrence of the maintenance event in the plurality of resources.
Systems, methods, and non-transitory computer readable media are provided for managing pipelines of operations on data. A system may access data and provide a set of functions for the data. The system may receive a user's selection of one or more functions from the set of functions. The system may generate a pipeline of operations for the data based on the user's selection. The pipeline of operations may include the function(s) selected by the user.
A system architecture can be used to facilitate communication among applications that are native and/or non-native to an application environment. The system architecture can include a first application environment executed on a client-side computing device. The first application environment can execute software applications that are native thereto. The first application environment can further execute software applications that are native thereto, but which software applications themselves comprise second application environments of types different from the first application environment, and which software applications can therefore execute additional software applications that are non-native to the first application environment. The first application environment can further execute a computation engine that is configured to store and execute instructions received from the first software application, the second software application, or both.
An apparatus, computer-implemented method and computer program are disclosed for performing a cryptographic operation in a high-trust (HT) environment. The HT environment including a compute service and key storage service. The compute service receives from a user device, a user request for performing a cryptographic operation on at least a portion of a large-scale dataset. The user request including a user token associated with a user of the user device. The compute service sends to the key storage service, a cryptographic key access request corresponding to the received user request. The cryptographic key access request including data representative of the user token and/or a compute service token. The key storage service determines from the user token and/or compute service token whether the user has permission to have the cryptographic operation performed and/or whether to grant the compute service access to data representative of the cryptographic key in relation to the requested cryptographic operation when user has permission. In response to the key storage service granting access to the compute service, the key storage service sends to the compute service the requested cryptographic key/algorithm associated with the cryptographic operation of the user request. The compute service performs the cryptographic operation on the portion of the large-scale dataset based on the received cryptographic key/algorithm.
Systems and methods are provided to retrieve or analyze usage data collected from a device or a facility where the device, optionally with devices are located, and identify useful features for making a diagnosis of the device. The diagnosis can be made before a system failure to reduce down time and inefficient use of the device, or after the system failure to expedite and facilitate diagnosis and repair. In addition to the usage data, such as energy and resource consumption, the system can also obtain information relating to the facility and the device's external environment which can be used for normalizing the usage data. Further, based on the diagnosis, the system can make suitable recommendations for repair, replacement, maintenance and upgrade.
An apparatus, computer-implemented method and computer program are disclosed for synchronising dataset updates. For example, the method may comprise providing a first code branch associated with a plurality of code sets which, when executed, produce respective time-series datasets for provision to a downstream process linked to the first code branch. The method may also comprise generating a second code branch, based on the first code branch, the second code branch executing the plurality of code sets as part of an updating process and, if successful, storing respective time-series datasets to respective memory locations associated with the second code branch. Another part of the method may comprise determining if all code sets executed by the second code branch have successfully committed. Responsive to a positive determination, one or more pointers, e.g. all pointers, associated with the first code branch may be updated to point to the respective memory locations associated with the second code branch in order that the respective successfully-committed time-series datasets are provided to the downstream process.
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
Systems and methods are provided for creating and managing a data integration workspace. The workspace may comprise one or more views of data (or datasets) stored in or accessible by the system. Models may be generated and updated based on the plurality of datasets and presented via a graphical user interface. Feedback received via a graphical user interface presenting a model may be used to annotate an underlying dataset associated with the model. Responsive to a modification of the underlying dataset or the rules for using the underlying dataset to generate the model, other related datasets and/or models may be automatically updated accordingly. Templates associated with one or more types of users may be defined. Each template may comprise one or more specific models related to a specific type of user.
G06T 11/20 - Drawing from basic elements, e.g. lines or circles
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
An example method of enforcing granular access policy for embedded artifacts comprises: detecting an association of an embedded artifact with a resource container; associating the embedded artifact with at least a subset of an access control policy associated with the resource container; and responsive to receiving an access request to access the embedded artifact, applying the access control policy associated with the resource container for determining whether the access request is grantable.
A method, performed by one or more processors, including: receiving one or more event records; generating, using the one or more event records, an event descriptor object descriptive of one or more events occurring in a networked system, wherein the event descriptor object comprises a plurality of event properties; receiving one or more entity records; generating, using the one or more entity records, an entity descriptor object descriptive of one or more entities relevant to the security of the networked system, wherein the entity descriptor object comprises a plurality of entity properties; incorporating, into an object graph, the event descriptor object and the entity descriptor object; and associating, in the object graph, the event descriptor object with the entity descriptor object using at least one of the plurality of event properties and at least one of the plurality of entity properties.
Systems and methods for performing sensor correlation by a plurality of edge devices are disclosed. For example, a method includes: receiving a first set of edge data from a first edge device of the plurality of edge devices; receiving a second set of edge data from a second edge device of the plurality of edge devices, the second edge device being different from the first edge device; analyzing the first set of edge data using one or more computing models to determine a first object detected in the first set of edge data; analyzing the second set of edge data using the one or more computing models to determine a second object detected in the second set of edge data; and determining whether the first object and the second object are a same object based upon one or more object parameters.
Systems and methods for implementing sequenced filter templates to intelligently reduce a dataset to find useful patterns and source data are disclosed. An expert investigative user may configure a filter template comprising a series of filters organized in a sequence desired by the expert user. The filter template can be customized by an end user to reduce a dataset and perform guide investigation of the reduced dataset.
A system and method for processing data wherein one or more user selections of source data and an input defining one or more operations to be performed on the selected source data are received to generate processed data for display as a chart; the source data is retrieved from at least one data source, the source data is processed according to the defined one or more operations to generate processed data for output for display as a chart, the chart is stored as data defining the one or more operations and data identifying the source data operated on, a further user selection is received to redisplay the chart; retrieving the source data from the at least one data source; and the source data is processed according to the defined one or more operations to generate the processed data for output for redisplay as the chart.
Disclosed herein are systems and methods for sensor cueing. In one example, the method includes: receiving a model inference from a computing model using a first set of sensor data, the model inference associated with a target object; generating a sensor command based at least in part upon the model inference, the sensor command comprising one or more object parameters associated with the target object and one or more sensor parameters associated with a sensor; and transmitting the sensor command to the sensor via a sensor API.
Systems and methods for using disparate data sets to attribute data to an entity are disclosed. Disparate data sets can be obtained from a variety of data sources. The disclosed systems and methods can obtain a first and second data set. Trajectories can represent multiple data records in a data set associated with an entity. Trajectories from the obtained data sets can be used to associate data stored among the various data sets. The association can be based on the agreement between the trajectories. The associated data records can further be used to associate the entities related to the associated data records.
Disclosed herein are systems and methods for model selection and update operation. The methods include receiving a model request with parameters selected from a group consisting of a type of computing model, a processing characteristic, and a data characteristic; receiving information associated with a plurality of computing models from a model repository; selecting one or more computing models based upon the model request; compiling a container request based on the model request and the one or more selected computing models; transmitting the container request to a container infrastructure; and coupling the one or more selected computing models to an artificial intelligence inference platform (AIP).
Systems and methods are provided for intelligently monitoring environments, classifying objects within such environments, detecting events within such environments, receiving and propagating input concerning image information from multiple users in a collaborative environment, identifying and responding to situational abnormalities or situations of interest based on such detections and/or user inputs.
A system including first computer memory storing a full data set representable in rows and columns, a second computer memory storing executable instructions, and processors configured to execute the instructions to cause presentation of data of the full data set on a display including columns of data each having data fields, receive user input identifying a column of the data set, determine items to modify in information in the data fields of the identified column, generate and cause display of an indication of a proposed change action to modify the determined items, and in response to a user input indicating a selection of the indication of the proposed change action, update the presentation of the data based on the change action to modify information displayed in the data fields of the identified column of the data, and store a log of the change action.
The programming notebook system, methods, and user interfaces described herein provide software developers with enhanced tools by which a programming notebook workflow and session history associated with code cells in a programming notebook may be tracked and maintained. As a developer progresses through a development workflow, the developer can select an option to save a program code card representing some or all of the program code cell inputs. A card editor user interface may present an aggregated listing of all program code the developer has provided across multiple code cells during the current session which the developer can edit, refine, and/or comment. The card editor may also allow the developer to add associated user interface code to display a UI component associated with the program code card, and allow the developer to add a description and tags for the card so that the card can be searched for and reused.
Various systems and methods are described herein for an improved spreadsheet application that allows a user to generate, manipulate, and replicate data visualizations (e.g., sparklines, graphs, charts, etc.) using functions without importing data into cells of the application. For example, data is stored in one or more remote or local data stores accessible to the improved spreadsheet application. A user enters a function into a cell of the improved spreadsheet application. The improved spreadsheet application generates a query using the function, the query identifying a portion of a dataset to retrieve from the data store(s). The improved spreadsheet application then transmits the query to the data store(s) and retrieves the requested data. A renderer of the improved spreadsheet application then renders a sparkline using the retrieved data. The improved spreadsheet application displays the rendered sparkline in the cell in which the function was entered, or at another designated location.
Systems are provided for managing access to a log of dataset that is generated when the dataset is accessed. A system stores, with respect to each of a log producer and a log accessor, an encrypted symmetric key for dataset that is encrypted using a corresponding public key. The system returns the encrypted symmetric key for the log producer, such that the log producer can decrypt the dataset that is encrypted using the symmetric key. A log of the dataset is generated when the log producer accesses the dataset.
G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
H04L 9/32 - Arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system
71.
SYSTEMS FOR NETWORK RISK ASSESSMENT INCLUDING PROCESSING OF USER ACCESS RIGHTS ASSOCIATED WITH A NETWORK OF DEVICES
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for network risk assessment. One of the methods includes obtaining information describing network traffic between a plurality of network devices within a network. A network topology of the network is determined based on the information describing network traffic, with the network topology including nodes connected by an edge to one or more other nodes, and with each node being associated with one or more network devices. Indications of user access rights of users are associated to respective nodes included in the network topology. User interface data associated with the network topology is generated.
H04L 41/0853 - Retrieval of network configuration; Tracking network configuration history by actively collecting configuration information or by backing up configuration information
H04L 43/0876 - Network utilisation, e.g. volume of load or congestion level
G06F 21/57 - Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
The present disclosure relates to methods and systems for querying data in a data repository. According to a first aspect, this disclosure describes a method of querying a database, comprising: receiving, at a computing device, a plurality of keywords; determining, by the computer device, a plurality of datasets relating to the keywords; identifying, by the computer device, metadata for the plurality of datasets indicating a relationship between the datasets by examining an ontology associated with the datasets; providing, by the computer device, one or more suggested database queries in natural language form, the one or more suggested database queries constructed based on the plurality of keywords and the metadata; receiving, by the computing device, a selection of the one or more suggested database queries; and constructing, by the computer device, an object view for the plurality of datasets based on the selected query and the metadata.
A method of securely deploying a software package comprises storing validity data describing restricted use of a restricted use token; receiving a command including a URL to deploy a software package; testing validity of the URL based on the validity data; and downloading, when the testing is successful, the software package via a secure channel, wherein the method is performed using one or more processors.
Systems and methods are provided for storing data representing respective sub-elements of a complex task. Data representing one or more links between two or more sub-elements is stored, the links indicating a dependency between said sub-elements. A work order is calculated based on the identified links. A graphical representation of the calculated work order which indicates said sub-elements and their dependencies is provided. The links may indicate a temporal dependency of a second sub-element on a first sub-element and in which the provided graphical representation presents the temporal relationship of the sub-elements. Historical data may be received for association with one or more selected links or sub-elements, the historical data related to a prior event and which affects the temporal relationship between the sub-elements. An updated work order modified by the historical data may be calculated. An updated graphical representation of the work order may be provided.
Described herein are systems, methods, and non-transitory computer readable media for validating or rejecting automated detections of an entity being tracked within an environment in order to generate a track representative of a travel path of the entity within the environment. The automated detections of the entity may be generated by an artificial intelligence (AI) algorithm. The track may represent a travel path of the tracked entity across a set of image frames. The track may contain one or more tracklets, where each tracklet includes a set of validated detections of the entity across a subset of the set of image frames and excludes any rejected detections of the entity. Each tracklet may also contain one or more user-provided detections in scenarios in which the tracked entity is observed or otherwise known to be present in an image frame but automated detection of the entity did not occur.
Various systems and methods are provided that detect malicious network tunneling. For example, VPN logs and data connection logs may be accessed. The VPN logs may list client IP addresses that have established a VPN connection with an enterprise network. The data connection logs may list client IP addresses that have requested connections external to the enterprise network and remote IP addresses to which connections are requested. The VPN logs and the data connection logs may be parsed to identify IP addresses that are present in the VPN logs as a client IP address and in the data connection logs as a remote IP address. If an IP address is so present, user data and traffic data associated with the IP address may be retrieved to generate a risk score. If the risk score exceeds a threshold, an alert to be displayed in a GUI is generated.
Various systems and methods are provided for performing soft entity resolution. A plurality of data objects are retrieved from a plurality of data stores to create aggregated data objects for one or more entities. One or more retrieved data objects may be associated with the same entity, based at least in part upon one or more attribute types and attribute values of the data objects. In response to a determination that the one or more of the retrieved data objects should be associated with the same entity, metadata is generated that associates the data objects with the entity, the metadata being stored separately from the data objects, such that the underlying data objects remain unchanged. In addition, one or more additional attributes may be determined for the entity, based upon the data objects associated with the entity.
Systems and methods for software distribution are disclosed. For example, the method includes: receiving a first deployment package for a first version of software; recursively disassembling the first deployment package into a plurality of components; accessing a set of second components of a second deployment package for a second version of the software; generating one or more component differentiations based at least in part upon the plurality of components associated with the first deployment package and the set of second components of the second deployment package, a first component differentiation of the one or more component differentiations being a difference between a first component associated with the first deployment package and a second component in the disassembled components of the second deployment package; and generating a distribution package based on the one or more component differentiations and a package structure associated with a component structure of the first deployment package.
A database system is described that includes components for storing time-series data and executing custom, user-defined computational expressions in substantially real-time such that the results can be provided to a user device for display in an interactive user interface. For example, the database system may process stored time-series data in response to requests from a user device. The request may include a start time, an end time, a period, and/or a computational expression. The database system may retrieve the time-series data identified by the computational expression and, for each period, perform the arithmetic operation(s) identified by the computational expression on data values corresponding to times within the start time and the end time. Once all new data values have been generated, the database system may transmit the new data values to the user device for display in the interactive user interface.
Methods and systems for collaboration between two or more parties to generate a model based on data from the parties without data to the another party. A system includes an aggregation system having computer storage devices configured to store a model and a plurality versions of an aggregated model, and instructions, and one or more processors configured to execute the plurality of computer readable instructions to, iteratively, receive a first updated model from a first system controlled by a first party and a second updated model from a second system controlled by a second party, determine changes from the first updated model and the second updated model to include in an aggregated model, communicate a version of the aggregated model to the first system and a version of the aggregated model to the second system, and store a final aggregated model.
G06N 3/098 - Distributed learning, e.g. federated learning
G06N 3/0442 - Recurrent networks, e.g. Hopfield networks characterised by memory or gating, e.g. long short-term memory [LSTM] or gated recurrent units [GRU]
82.
PERFORMING DATABASE JOINS IN DISTRIBUTED DATA PROCESSING SYSTEMS
A computer-implemented method for efficiently performing a database join in a distributed data processing system comprising multiple computational nodes, the method comprising determining a first set of one or more columns of a first database table and a second set of one or more columns of a second database table on which the join is to be performed; estimating a size of the rows of the first table which have a particular combination of values in the first set of columns; computing a salt factor n based on the estimated size of rows and further based on a processing capacity of a computational node of the distributed data processing system; assigning one of n different salt values to each row of the first table having the particular combination of values in the first set of columns; for each row of the second table having the particular combination of values in the second set of columns into n rows, expanding the row into n row, and assigning to each expanded row a different one of the n salt values; and performing a join operation on the modified first and second tables, wherein the rows of the first and second tables have the same combination of values in the first and second sets of columns and the same salt value are joined on the same computational node.
Methods and systems for providing a user interface and workflow for interacting with time series data, and applying portions of time series data sets for refining regression models. A system can present a user interface for receiving a first user input selecting a first model from a list of models for modeling the apparatus, generate and display a first chart depicting a first time series data set depicting data from a first sensor, generate and display a second chart depicting a second time series data set depicting a target output of the apparatus, receive a second user input of a portion of the first time series data set, and generate and display a third chart depicting a third time series data set depicting an output of the selected model and aligned with the second chart of the target output and updated in real-time in response to the second user input.
A computer system provides transaction-level data retention policy inheritance. The system may perform operations including storing a first dataset comprising a plurality of transactions, each of the plurality of transactions comprising one or more data items; receiving a first transaction to the first dataset, the first transaction comprising one or more data items; determining a first retention policy for the first transaction; and storing the first retention policy with the first transaction. The system may further perform operations including calculating a deletion date for the first transaction based on the first retention policy; and storing the deletion date with the first transaction in the first dataset.
A resource dependency system and its associated user interfaces, used for tracking data dependencies and data transformations between resources, may display visual node graphs with resources as nodes and the data dependencies and data transformations associated with the columns as edges between the nodes. The nodes representing the resources may be displayed differently based on relevant differences in the resources they represent, which can be set through various selectable criteria and schemes. The user interfaces may include selectable options for visually arranging the nodes or grouping the nodes into superseding nodes according to how the nodes are displayed or the relevant differences in the resources they represent. Updated properties and data dependencies associated with superseding nodes can be presented to the user.
Systems and methods are provided for improved graphical user interfaces. The system enables multiple separate applications, each of which may typically be in their own separate window or tab, to be interacted within a single window, such as a tab of a web browser application. The main window includes smaller sub-windows that can correspond to a distinct application with its own graphical user interface. A large sub-window within the main window is opened for the primary application where the user is currently interacting with a graphical user interface of the primary application. The user then is able to switch between applications (all within the same main window) and applications that are no longer being used can be minimized in smaller sub-windows off to the side of the primary sub-window. The system enables a user to drag and drop an item from one sub-window to another sub-window. Some of the interactions between the windows and data transformations are stored and can be visually presented in a graph.
G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
G06F 9/451 - Execution arrangements for user interfaces
G06F 3/048 - Interaction techniques based on graphical user interfaces [GUI]
Systems and methods for identifying associations between a code snippet query and stored computer code stored. The method can receive a code query identifying a code snippet to search for, determine a fingerprint of the query code snippet, and search the stored software using the fingerprint to identify software results of code similar to the query code snippet. The fingerprint can be determined by generating k-grams of the code snippet. The k-grams used for the search can be down-selected based on a winnowing process. The method can remove from the software results code that is associated with sanctioned software. The method can include coalescing the software results to produce a subset of the software results, generating a code search user interface comprising information indicative of the subset of software results, and causing presentation of the code search user interface and displaying the subset of software results.
Systems, methods, and non-transitory computer readable media are provided for providing category-sensitive chat channels. A category-sensitive chat channel may be provided. The category-sensitive chat channel may be assigned a given category level. The given category level may determine a scope of content allowed in the category-sensitive chat channel. Information to be posted through the category-sensitive chat channel may be obtained. The obtained information may be filtered based on the given category level. The filtered information may be posted in the category-sensitive chat channel.
A computer-implemented method for targeted sweep of a key-value data storage is provided. The method comprises before a write transaction to a database having a key value store commits, and before each of one or more write commands of the write transaction are persisted to the key value store, writing an entry for each of the one or more write commands to an end of a targeted sweep queue, the entry comprising metadata including: data identifying a cell to which the write command relates, a start timestamp of the write transaction, and information identifying a type of the write transaction.
Activities related to data analyses are managed in part using task objects representing tasks that need to be performed. In one embodiment, a method comprises: receiving a first request to generate a task object that describes a task; responsive to the first request, generating the task object, the task object being a data structure that comprises values for task object fields that represent attributes of the task; identifying, in a repository of data objects, a particular data object to associate with the task object; determining that a first field of the task object fields corresponds to a second field of the particular data object, the second field of the particular data object having a particular value; and assigning the first field of the task object to the particular value of the corresponding second field. In another embodiment, task objects are associated with geolocation data, and mapped or otherwise presented accordingly.
A method comprises storing an ontology for a data store, wherein the ontology comprises a plurality of data object types and a plurality of object property types. The method also comprises storing a validator for a particular object property type of the plurality of object property types, wherein the validator specifies a permitted value for the particular object property type, and storing a parser definition corresponding to the particular object property type, wherein the parser definition specifying a permitted format for the particular object property type. In addition, the method comprises receiving user input that changes a particular data object type of the plurality of data object types, including changing the particular object property type. Finally, the method comprises updating the validator for the particular object property type, and updating the parser definition corresponding to the particular object property type.
Computing systems methods, and non-transitory storage media are provided for retrieving information regarding an operation to be performed by a platform, performing a preliminary validation of the operation, generating details regarding the preliminary validation, transmitting at least a subset of the details of the preliminary validation to the platform, and populating the generated details on an interface. If the preliminary validation fails, the platform refrains from performing the operation. Furthermore, the logic describing the operation can be executed on different platforms and is not bound or limited to one platform.
System and method for isolating network traffic of multiple users across a network of a computing platform. For example, a method includes receiving data at a networking device of a computing platform. The networking device includes a plurality of routing tables. Each routing table of the plurality of routing tables is associated with a different user of multiple users of the computing platform. A user of the multiple users is identified based at least in part on the received data. In response to identifying the user of the multiple users based at least in part on the received data, a routing table of the plurality of routing tables is identified based at least in part on the identified user. A route from the identified routing table is determined based at least in part on the received data. The received data is sent across a network of the computing platform according to the determined route. The method is performed using one or more processors.
Systems and methods are provided for identifying relationships between defects. The system may obtain defect items and associated information. Defect items may be compared to one another based on their attributes to determine how related they are. According to the comparisons, defect items may be grouped together into issue items for further analysis by a user. The system may further update a defect comparison model according to user interaction with defect items.
42 - Scientific, technological and industrial services, research and design
Goods & Services
Business data analysis; business consulting services; business information services; providing business intelligence services; business data and information consulting services; compilation and systematization of information into computer databases; systemization of data in computer databases; compilation of statistics; data processing services; updating and maintenance of data in computer databases; database management; computerized database management; business consulting services in the field of enterprise architecture; business risk management consultation; government data analysis; government consulting services; government information services; providing government intelligence services; government data and information consulting services; government consulting services in the field of enterprise architecture; government risk management consultation Software; software as a service (SaaS); platform as a service (PaaS); infrastructure as a service (IaaS); accreditation as a service (AaaS); providing temporary use of online non-downloadable software for developing, implementing, deploying and processing algorithms; providing temporary use of online non-downloadable software for developing, implementing, deploying and processing connected algorithms; providing temporary use of online non-downloadable software for developing, training, managing and deploying artificial intelligence models and large language models (LLM); providing temporary use of online non-downloadable edge artificial intelligence software for processing data via a distributed computing framework; providing temporary use of online non-downloadable software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining; providing temporary use of online non-downloadable artificial intelligence software for machine learning, deep learning, natural language generation, statistical learning, supervised learning, unsupervised learning, large language models (LLM), data mining, predictive analytics, business intelligence, and computer vision; providing temporary use of online non-downloadable software, namely, software for knowledge-based artificial intelligence platforms, data analytics platforms, and automation platforms for use in the fields of artificial intelligence, machine learning, deep learning, statistical learning, supervised learning, un-supervised learning, large language models (LLM), data mining, predictive analytics and business intelligence; providing temporary use of online non-downloadable simulation, modeling and data processing software for use in data visualization, data analysis, data mining, data interpretation, predictive analytics, accessing and editing large-scale data, interactive visual computing, and design of information graphics; providing temporary use of online non-downloadable software for information and data integration, analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, security, and tracking of data and information; providing temporary use of online non-downloadable hosting software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining; providing temporary use of online non-downloadable software for analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, security, and tracking of geospatial, map and location data and information; providing temporary use of online non-downloadable hosting software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining of geospatial, map and location data and information; providing temporary use of online non-downloadable software for deploying, distributing, configuring, testing, monitoring, installing, upgrading, updating, patching, supporting, enabling, and managing other software; providing temporary use of online non-downloadable software for use in securing other software by monitoring, tracking, and logging network configuration, performance, activity, and events; providing temporary use of online non-downloadable software for analyzing, monitoring and understanding software system health and anticipating future software issues; providing temporary use of online non-downloadable software for monitoring and managing software infrastructure security; providing temporary use of online non-downloadable software for use in cloud infrastructure management and automation; providing temporary use of online non-downloadable software for use in platform infrastructure management and automation; providing temporary use of online non-downloadable software for data and application migration; providing temporary use of online non-downloadable software for platform and infrastructure migration; providing temporary use of online non-downloadable software for monitoring, tracking, logging and analyzing cloud, software and network configuration, performance, activity, and events; providing temporary use of online non-downloadable software for use in automating software installation, management and configuration; providing temporary use of online non-downloadable software for use in continuous delivery of application, platform or infrastructure installations, upgrades or configurations; providing temporary use of online non-downloadable software for use in management of installations across different environments; providing temporary use of online non-downloadable software in the field of knowledge management to host computer application software for the collection, organizing, modifying, book marking, transmission, storage and sharing of data and information; providing temporary use of online non-downloadable software for protecting, scanning, detecting, quarantining, and ensuring the security of software and computer application infrastructure; providing temporary use of online non-downloadable software for providing an application marketplace; providing temporary use of online non-downloadable application marketplace software featuring software applications of others; providing temporary use of online non-downloadable software for hosting computer software applications of others; providing temporary use of online non-downloadable software for hosting computer software applications of others; providing temporary use of online non-downloadable software for enabling and managing regulatory compliance and security accreditation and certification; providing temporary use of online non-downloadable software for providing accredited software as a service (SaaS), platform as a service (PaaS), and infrastructure as a service (IaaS) environments in compliance with established regulations and standards; providing temporary use of online non-downloadable software for providing virtual computer environments for software as a service (SaaS), platform as a service (PaaS), and infrastructure as a service (IaaS) functions; providing temporary use of online non-downloadable software for providing accreditation for software as a service (SaaS) solutions; providing temporary use of online non-downloadable software for building, deploying, hosting, securing, operating, integrating, and managing containerized applications on cloud computing platforms; providing temporary use of online non-downloadable software for regulatory compliance; providing temporary use of online non-downloadable software for compliance with established accreditation standards and other national standards and regulations; providing temporary use of online non-downloadable software for security monitoring, vulnerability scanning, access control, authentication, and encryption; providing temporary use of online non-downloadable software for use in the field of government; software as a service (SaaS) services featuring software for developing, implementing, deploying and processing algorithms; software as a service (SaaS) services featuring software for developing, implementing, deploying and processing connected algorithms; software as a service (SaaS) services featuring software for developing, training, managing and deploying artificial intelligence models and large language models (LLM); software as a service (SaaS) services featuring edge artificial intelligence software for processing data via a distributed computing framework; software as a service (SaaS) services featuring software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining; software as a service (SaaS) services featuring artificial intelligence software for machine learning, deep learning, natural language generation, statistical learning, supervised learning, unsupervised learning, large language models (LLM), data mining, predictive analytics, business intelligence, and computer vision; software as a service (SaaS) services featuring software for knowledge-based artificial intelligence platforms, data analytics platforms, and automation platforms for use in the fields of artificial intelligence, machine learning, deep learning, statistical learning, supervised learning, un-supervised learning, large language models (LLM), data mining, predictive analytics and business intelligence; software as a service (SaaS) services featuring simulation, modeling and data processing software for use in data visualization, data analysis, data mining, data interpretation, predictive analytics, accessing and editing large-scale data, interactive visual computing, and design of information graphics; software as a service (SaaS) services featuring software for information and data integration, analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, security, and tracking of data and information; software as a service (SaaS) services featuring software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining; software as a service (SaaS) services featuring software for analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, security, and tracking of geospatial, map and location data and information; software as a service (SaaS) services featuring hosting software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining of geospatial, map and location data and information; software as a service (SaaS) services featuring software for deploying, distributing, configuring, testing, monitoring, installing, upgrading, updating, patching, supporting, enabling, and managing other software; software as a service (SaaS) services featuring software for use in securing other software by monitoring, tracking, and logging network configuration, performance, activity, and events; software as a service (SaaS) services featuring software for analyzing, monitoring and understanding software system health and anticipating future software issues; software as a service (SaaS) services featuring software for monitoring and managing software infrastructure security; software as a service (SaaS) services featuring software for use in cloud infrastructure management and automation; software as a service (SaaS) services featuring software for use in platform infrastructure management and automation; software as a service (SaaS) services featuring software for data and application migration; software as a service (SaaS) services featuring software for platform and infrastructure migration; software as a service (SaaS) services featuring software for monitoring, tracking, logging and analyzing cloud, software and network configuration, performance, activity, and events; software as a service (SaaS) services featuring software for use in automating software installation, management and configuration; software as a service (SaaS) services featuring software for use in continuous delivery of application, platform or infrastructure installations, upgrades or configurations; software as a service (SaaS) services featuring software for use in management of installations across different environments; software as a service (SaaS) services featuring software in the field of knowledge management to host computer application software for the collection, organizing, modifying, book marking, transmission, storage and sharing of data and information; software as a service (SaaS) services featuring software for protecting, scanning, detecting, quarantining, and ensuring the security of software and computer application infrastructure; software as a service (SaaS) services featuring software for providing an application marketplace; software as a service (SaaS) services featuring application marketplace software featuring software applications of others; software as a service (SaaS) services featuring software for hosting computer software applications of others; software as a service (SaaS) services featuring software for hosting computer software applications of others; software as a service (SaaS) services featuring software for enabling and managing regulatory compliance and security accreditation and certification; software as a service (SaaS) services featuring software for providing accredited software as a service (SaaS), platform as a service (PaaS), and infrastructure as a service (IaaS) environments in compliance with established regulations and standards; software as a service (SaaS) services featuring software for providing virtual computer environments for software as a service (SaaS), platform as a service (PaaS), and infrastructure as a service (IaaS) functions; software as a service (SaaS) services featuring software for providing accreditation for software as a service (SaaS) solutions; software as a service (SaaS) services featuring software for building, deploying, hosting, securing, operating, integrating, and managing containerized applications on cloud computing platforms; software as a service (SaaS) services featuring software for regulatory compliance; software as a service (SaaS) services featuring software for compliance with established accreditation standards and other national standards and regulations; software as a service (SaaS) services featuring software for security monitoring, vulnerability scanning, access control, authentication, and encryption; software as a service (SaaS) services featuring software for use in the field of government; platform as a service (PaaS) services featuring software for developing, implementing, deploying and processing algorithms; platform as a service (PaaS) services featuring software for developing, implementing, deploying and processing connected algorithms; platform as a service (PaaS) services featuring software for developing, training, managing and deploying artificial intelligence models and large language models (LLM); platform as a service (PaaS) services featuring edge artificial intelligence software for processing data via a distributed computing framework; platform as a service (PaaS) services featuring software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining; platform as a service (PaaS) services featuring artificial intelligence software for machine learning, deep learning, natural language generation, statistical learning, supervised learning, unsupervised learning, large language models (LLM), data mining, predictive analytics, business intelligence, and computer vision; platform as a service (PaaS) services featuring software for knowledge-based artificial intelligence platforms, data analytics platforms, and automation platforms for use in the fields of artificial intelligence, machine learning, deep learning, statistical learning, supervised learning, un-supervised learning, large language models (LLM), data mining, predictive analytics and business intelligence; platform as a service (PaaS) services featuring simulation, modeling and data processing software for use in data visualization, data analysis, data mining, data interpretation, predictive analytics, accessing and editing large-scale data, interactive visual computing, and design of information graphics; platform as a service (PaaS) services featuring software for information and data integration, analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, security, and tracking of data and information; platform as a service (PaaS) services featuring software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining; platform as a service (PaaS) services featuring software for analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, security, and tracking of geospatial, map and location data and information; platform as a service (PaaS) services featuring hosting software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining of geospatial, map and location data and information; platform as a service (PaaS) services featuring software for deploying, distributing, configuring, testing, monitoring, installing, upgrading, updating, patching, supporting, enabling, and managing other software; platform as a service (PaaS) services featuring software for use in securing other software by monitoring, tracking, and logging network configuration, performance, activity, and events; platform as a service (PaaS) services featuring software for analyzing, monitoring and understanding software system health and anticipating future software issues; platform as a service (PaaS) services featuring software for monitoring and managing software infrastructure security; platform as a service (PaaS) services featuring software for use in cloud infrastructure management and automation; platform as a service (PaaS) services featuring software for use in platform infrastructure management and automation; platform as a service (PaaS) services featuring software for data and application migration; platform as a service (PaaS) services featuring software for platform and infrastructure migration; platform as a service (PaaS) services featuring software for monitoring, tracking, logging and analyzing cloud, software and network configuration, performance, activity, and events; platform as a service (PaaS) services featuring software for use in automating software installation, management and configuration; platform as a service (PaaS) services featuring software for use in continuous delivery of application, platform or infrastructure installations, upgrades or configurations; platform as a service (PaaS) services featuring software for use in management of installations across different environments; platform as a service (PaaS) services featuring software in the field of knowledge management to host computer application software for the collection, organizing, modifying, book marking, transmission, storage and sharing of data and information; platform as a service (PaaS) services featuring software for protecting, scanning, detecting, quarantining, and ensuring the security of software and computer application infrastructure; platform as a service (PaaS) services featuring software for providing an application marketplace; platform as a service (PaaS) services featuring application marketplace software featuring software applications of others; platform as a service (PaaS) services featuring software for hosting computer software applications of others; platform as a service (PaaS) services featuring software for hosting computer software applications of others; platform as a service (PaaS) services featuring software for enabling and managing regulatory compliance and security accreditation and certification; platform as a service (PaaS) services featuring software for providing accredited software as a service (SaaS), platform as a service (PaaS), and infrastructure as a service (IaaS) environments in compliance with established regulations and standards; platform as a service (PaaS) services featuring software for providing virtual computer environments for software as a service (SaaS), platform as a service (PaaS), and infrastructure as a service (IaaS) functions; platform as a service (PaaS) services featuring software for providing accreditation for software as a service (SaaS) solutions; platform as a service (PaaS) services featuring software for building, deploying, hosting, securing, operating, integrating, and managing containerized applications on cloud computing platforms; platform as a service (PaaS) services featuring software for regulatory compliance; platform as a service (PaaS) services featuring software for compliance with established accreditation standards and other national standards and regulations; platform as a service (PaaS) services featuring software for security monitoring, vulnerability scanning, access control, authentication, and encryption; platform as a service (PaaS) services featuring software for use in the field of government; infrastructure as a service (IaaS) services featuring software for developing, implementing, deploying and processing algorithms; infrastructure as a service (IaaS) services featuring software for developing, implementing, deploying and processing connected algorithms; infrastructure as a service (IaaS) services featuring software for developing, training, managing and deploying artificial intelligence models and large language models (LLM); infrastructure as a service (IaaS) services featuring edge artificial intelligence software for processing data via a distributed computing framework; infrastructure as a service (IaaS) services featuring software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining; infrastructure as a service (IaaS) services featuring artificial intelligence software for machine learning, deep learning, natural language generation, statistical learning, supervised learning, unsupervised learning, large language models (LLM), data mining, predictive analytics, business intelligence, and computer vision; infrastructure as a service (IaaS) services featuring software for knowledge-based artificial intelligence platforms, data analytics platforms, and automation platforms for use in the fields of artificial intelligence, machine learning, deep learning, statistical learning, supervised learning, un-supervised learning, large language models (LLM), data mining, predictive analytics and business intelligence; infrastructure as a service (IaaS) services featuring simulation, modeling and data processing software for use in data visualization, data analysis, data mining, data interpretation, predictive analytics, accessing and editing large-scale data, interactive visual computing, and design of information graphics; infrastructure as a service (IaaS) services featuring software for information and data integration, analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, security, and tracking of data and information; infrastructure as a service (IaaS) services featuring software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining; infrastructure as a service (IaaS) services featuring software for analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, security, and tracking of geospatial, map and location data and information; infrastructure as a service (IaaS) services featuring hosting software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining of geospatial, map and location data and information; infrastructure as a service (IaaS) services featuring software for deploying, distributing, configuring, testing, monitoring, installing, upgrading, updating, patching, supporting, enabling, and managing other software; infrastructure as a service (IaaS) services featuring software for use in securing other software by monitoring, tracking, and logging network configuration, performance, activity, and events; infrastructure as a service (IaaS) services featuring software for analyzing, monitoring and understanding software system health and anticipating future software issues; infrastructure as a service (IaaS) services featuring software for monitoring and managing software infrastructure security; infrastructure as a service (IaaS) services featuring software for use in cloud infrastructure management and automation; infrastructure as a service (IaaS) services featuring software for use in platform infrastructure management and automation; infrastructure as a service (IaaS) services featuring software for data and application migration; infrastructure as a service (IaaS) services featuring software for platform and infrastructure migration; infrastructure as a service (IaaS) services featuring software for monitoring, tracking, logging and analyzing cloud, software and network configuration, performance, activity, and events; infrastructure as a service (IaaS) services featuring software for use in automating software installation, management and configuration; infrastructure as a service (IaaS) services featuring software for use in continuous delivery of application, platform or infrastructure installations, upgrades or configurations; infrastructure as a service (IaaS) services featuring software for use in management of installations across different environments; infrastructure as a service (IaaS) services featuring software in the field of knowledge management to host computer application software for the collection, organizing, modifying, book marking, transmission, storage and sharing of data and information; infrastructure as a service (IaaS) services featuring software for protecting, scanning, detecting, quarantining, and ensuring the security of software and computer application infrastructure; infrastructure as a service (IaaS) services featuring software for providing an application marketplace; infrastructure as a service (IaaS) services featuring application marketplace software featuring software applications of others; infrastructure as a service (IaaS) services featuring software for hosting computer software applications of others; infrastructure as a service (IaaS) services featuring software for hosting computer software applications of others; infrastructure as a service (IaaS) services featuring software for enabling and managing regulatory compliance and security accreditation and certification; infrastructure as a service (IaaS) services featuring software for providing accredited software as a service (SaaS), platform as a service (PaaS), and infrastructure as a service (IaaS) environments in compliance with established regulations and standards; infrastructure as a service (IaaS) services featuring software for providing virtual computer environments for software as a service (SaaS), platform as a service (PaaS), and infrastructure as a service (IaaS) functions; infrastructure as a service (IaaS) services featuring software for providing accreditation for software as a service (SaaS) solutions; infrastructure as a service (IaaS) services featuring software for building, deploying, hosting, securing, operating, integrating, and managing containerized applications on cloud computing platforms; infrastructure as a service (IaaS) services featuring software for regulatory compliance; infrastructure as a service (IaaS) services featuring software for compliance with established accreditation standards and other national standards and regulations; infrastructure as a service (IaaS) services featuring software for security monitoring, vulnerability scanning, access control, authentication, and encryption; infrastructure as a service (IaaS) services featuring software for use in the field of government; accreditation as a service (AaaS) services featuring software for developing, implementing, deploying and processing algorithms; accreditation as a service (AaaS) services featuring software for developing, implementing, deploying and processing connected algorithms; accreditation as a service (AaaS) services featuring software for developing, training, managing and deploying artificial intelligence models and large language models (LLM); accreditation as a service (AaaS) services featuring edge artificial intelligence software for processing data via a distributed computing framework; accreditation as a service (AaaS) services featuring software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining; accreditation as a service (AaaS) services featuring artificial intelligence software for machine learning, deep learning, natural language generation, statistical learning, supervised learning, unsupervised learning, large language models (LLM), data mining, predictive analytics, business intelligence, and computer vision; accreditation as a service (AaaS) services featuring software for knowledge-based artificial intelligence platforms, data analytics platforms, and automation platforms for use in the fields of artificial intelligence, machine learning, deep learning, statistical learning, supervised learning, un-supervised learning, large language models (LLM), data mining, predictive analytics and business intelligence; accreditation as a service (AaaS) services featuring simulation, modeling and data processing software for use in data visualization, data analysis, data mining, data interpretation, predictive analytics, accessing and editing large-scale data, interactive visual computing, and design of information graphics; accreditation as a service (AaaS) services featuring software for information and data integration, analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, security, and tracking of data and information; accreditation as a service (AaaS) services featuring software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining; accreditation as a service (AaaS) services featuring software for analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, security, and tracking of geospatial, map and location data and information; accreditation as a service (AaaS) services featuring hosting software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining of geospatial, map and location data and information; accreditation as a service (AaaS) services featuring software for deploying, distributing, configuring, testing, monitoring, installing, upgrading, updating, patching, supporting, enabling, and managing other software; accreditation as a service (AaaS) services featuring software for use in securing other software by monitoring, tracking, and logging network configuration, performance, activity, and events; accreditation as a service (AaaS) services featuring software for analyzing, monitoring and understanding software system health and anticipating future software issues; accreditation as a service (AaaS) services featuring software for monitoring and managing software infrastructure security; accreditation as a service (AaaS) services featuring software for use in cloud infrastructure management and automation; accreditation as a service (AaaS) services featuring software for use in platform infrastructure management and automation; accreditation as a service (AaaS) services featuring software for data and application migration; accreditation as a service (AaaS) services featuring software for platform and infrastructure migration; accreditation as a service (AaaS) services featuring software for monitoring, tracking, logging and analyzing cloud, software and network configuration, performance, activity, and events; accreditation as a service (AaaS) services featuring software for use in automating software installation, management and configuration; accreditation as a service (AaaS) services featuring software for use in continuous delivery of application, platform or infrastructure installations, upgrades or configurations; accreditation as a service (AaaS) services featuring software for use in management of installations across different environments; accreditation as a service (AaaS) services featuring software in the field of knowledge management to host computer application software for the collection, organizing, modifying, book marking, transmission, storage and sharing of data and information; accreditation as a service (AaaS) services featuring software for protecting, scanning, detecting, quarantining, and ensuring the security of software and computer application infrastructure; accreditation as a service (AaaS) services featuring software for providing an application marketplace; accreditation as a service (AaaS) services featuring application marketplace software featuring software applications of others; accreditation as a service (AaaS) services featuring software for hosting computer software applications of others; accreditation as a service (AaaS) services featuring software for hosting computer software applications of others; accreditation as a service (AaaS) services featuring software for enabling and managing regulatory compliance and security accreditation and certification; accreditation as a service (AaaS) services featuring software for providing accredited software as a service (SaaS), platform as a service (PaaS), and infrastructure as a service (IaaS) environments in compliance with established regulations and standards; accreditation as a service (AaaS) services featuring software for providing virtual computer environments for software as a service (SaaS), platform as a service (PaaS), and infrastructure as a service (IaaS) functions; accreditation as a service (AaaS) services featuring software for providing accreditation for software as a service (SaaS) solutions; accreditation as a service (AaaS) services featuring software for building, deploying, hosting, securing, operating, integrating, and managing containerized applications on cloud computing platforms; accreditation as a service (AaaS) services featuring software for regulatory compliance; accreditation as a service (AaaS) services services featuring software for compliance with established accreditation standards and other national standards and regulations; accreditation as a service (AaaS) services featuring software for security monitoring, vulnerability scanning, access control, authentication, and encryption; accreditation as a service (AaaS) services featuring software for use in the field of government; application service provider (ASP); computer software for application development, testing, deployment and management; computer software for monitoring cloud and application performance; computer software development tools; software development kits (SDK); computer software for use in cloud infrastructure management and automation; computer software for running cloud computing based applications; data processing computer software; computer services, namely, enforcing, restricting and controlling access privileges of users of computing and network resources based on assigned credentials; computer services, namely, intrusion detection and protection; providing virtual computer systems and virtual computer environments through cloud computing; administering and maintaining virtual computing environments for others; software as a service (SaaS) featuring software for managing and deploying virtual machines to a cloud computing platform
Systems and methods are provided for obtaining information from at least one computing system, the information including a set of records that respectively identify at least a network-based address of a computing device that accessed the computing system and an account hosted by the computing system that was accessed using the computing device; determining at least a first account and a second account were accessed from one or more computing devices that share a given network-based address based at least in part on the obtained information; and associating the first account and the second account with the network-based address.
Computing systems methods, and non-transitory storage media are provided for obtaining an audio stream, converting the audio stream to an intermediate representation, performing diarization on the audio stream, separating the audio stream into individual speech constructs, performing speech recognition on the individual speech constructs by mapping each of the individual speech constructs, or consecutive individual speech constructs, to entries within a dictionary, to generate a transcription of the audio stream, generating an output indicative of the transcription and a result of the diarization, transforming the output into an object-based representation, and performing one or more operations on the object-based representation
G10L 17/02 - Preprocessing operations, e.g. segment selection; Pattern representation or modelling, e.g. based on linear discriminant analysis [LDA] or principal components; Feature selection or extraction
G10L 15/04 - Segmentation; Word boundary detection
G10L 15/22 - Procedures used during a speech recognition process, e.g. man-machine dialog
Streaming of shared state date from a presenter device to one or more viewer devices may be accomplished by shared state of a file (e.g., state of a presentation and/or the application that is displaying Information from the file and/or data related to the particular shared streaming of the presentation) rather than a screen share view of the application and/or file.
H04L 65/401 - Support for services or applications wherein the services involve a main real-time session and one or more additional parallel real-time or time sensitive sessions, e.g. white board sharing or spawning of a subconference
G06Q 10/101 - Collaborative creation, e.g. joint development of products or services
100.
SERVER IMPLEMENTED GEOGRAPHIC INFORMATION SYSTEM WITH GRAPHICAL INTERFACE
Example embodiments described herein pertain to a geographic information system (GIS), configured to obtain geospatial data representing a geographic area, assign a projection and coordinate system to the geospatial data, apply a transformation to the geospatial data, and generate a tile cache based on the transformed geospatial data, the tile cache including the determined projection and coordinate system.
