An electronic garage shelf is described. The system includes an electronic garage shelf which may be a metaphor for a shelf in a garage that is used to store parts for a vehicle. Merely for example, the electronic garage shelf may store a token part that signifies a part or smart component such as an oil filter, carburetor, spark plug, on a garage shelf in the user's garage. Further, the metaphor for a shelf in the garage may be expanded to include a virtual part that represents a part or smart component the user wants to acquire. Accordingly, the system may include garage shelf information comprised of virtual part information and token part information where the virtual part information may store virtual parts signifying parts that are desirable for acquisition and the token part information may store token parts signifying parts that are in the possession of the user.
Vehicles and other items often have corresponding documentation, such as registration cards, that includes a significant amount of informative textual information that can be used in identifying the item. Traditional OCR may be unsuccessful when dealing with non-cooperative images. Accordingly, features such as dewarping, text alignment, and line identification and removal may aid in OCR of non-cooperative images. Dewarping involves determining curvature of a document depicted in an image and processing the image to dewarp the image of the document to make it more accurately conform to the ideal of a cooperative image. Text alignment involves determining an actual alignment of depicted text, even when the depicted text is not aligned with depicted visual cues. Line identification and removal involves identifying portions of the image that depict lines and removing those lines prior to OCR processing of the image.
Systems and methods for providing a service experience score at a merchant physical location include a system provider device that determines, through communication at least one of a plurality of beacon devices located at the merchant physical location and a user device, a start of a user service experience. The system provider device also determines, through the at least one of the plurality of beacon devices and the user device, an end of the user service experience. A service experience score that is based at least partly on the start of the user service experience and the end of the user service experience is generated. The service experience score is stored in a database in association with a merchant that is associated with the merchant physical location. Subsets of the service experience score may be associated with different locations of the merchant physical location.
09 - Scientific and electric apparatus and instruments
35 - Advertising and business services
36 - Financial, insurance and real estate services
39 - Transport, packaging, storage and travel services
42 - Scientific, technological and industrial services, research and design
Goods & Services
Computer software for online commerce, online marketplace, and online auction services; Downloadable and recorded computer e-commerce software to allow users to conduct electronic business transactions in online marketplaces websites via a global computer network Online commerce, online marketplace, and online auction services; Provision of an on-line marketplace for buyers and sellers of goods and/or services Vault services for storing high value collectibles; safe deposit box services Storage of high value collectibles Non-downloadable computer software for online commerce, online marketplace, and online auction services; Electronic data storage; Providing temporary use of online, non-downloadable e-commerce software to allow users to conduct electronic business transactions in online marketplaces via a global computer network
09 - Scientific and electric apparatus and instruments
35 - Advertising and business services
36 - Financial, insurance and real estate services
39 - Transport, packaging, storage and travel services
42 - Scientific, technological and industrial services, research and design
Goods & Services
Computer software for online commerce, online marketplace, and online auction services; Downloadable and recorded computer e-commerce software to allow users to conduct electronic business transactions in online marketplaces websites via a global computer network Online commerce, online marketplace, and online auction services; Provision of an on-line marketplace for buyers and sellers of goods and/or services Vault services for storing high value collectibles; Safe deposit box services Storage of high value collectibles Non-downloadable computer software for online commerce, online marketplace, and online auction services; Electronic data storage; Providing temporary use of online, non-downloadable e-commerce software to allow users to conduct electronic business transactions in online marketplaces via a global computer network
6.
ADAPTIVE SECURITY FOR SMART CONTRACTS USING HIGH GRANULARITY METRICS
Technologies are shown for high granularity metric (HGM)-based control for smart contract execution. In accordance with some aspects, a function call associated with one or more methods of a smart contract on a blockchain is detected by identifying an entrance or exit of the function call in a kernel for smart contract execution on the blockchain. The function call is added to a function call stack, and one or more detected HGMs are identified in the function call stack. A comparison of the detected HGMs in the function call stack against one or more control rules is performed. Execution or completion of the function call is blocked based on the comparison.
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
G06Q 20/36 - Payment architectures, schemes or protocols characterised by the use of specific devices using electronic wallets or electronic money safes
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
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]
A rack mountable bracket is described. The bracket is mountable to a rack configured for mounting equipment. The rack is also configured according to a rack standard (e.g., EIA-310) that specifies how rails of the rack are disposed, one rail to another, and how a strip of holes disposed along a length of each rail is spaced, one hole to another. In one or more implementations, the bracket includes a pair of mounting edges for mounting the bracket to a mounting pair of the rails using hole strips of the mounting pair of rails. The bracket also includes an equipment mounting rail having a hole strip disposed along a length of the rail with holes spaced according to the rack standard. The equipment mounting rail is disposed between the mounting edges, such that when the bracket is mounted to the mounting pair of rails the bracket is horizontally oriented.
Dynamic link preview generation techniques are described that overcome the challenges of conventional techniques by supporting link preview generation by a content provider system that proves the digital content via a respective network address. In one example, a content provider system, based on a request received from a service provider system, identifies a communication platform of the service provider system that is to be used to communicate the shared link. Upon identifying the communication platform, the content provider system locates customization data that describes how the link preview is to be generated for the communication platform. In response, the content provider system renders digital content available via the network address to generate the link preview.
Various embodiments improve search technologies and computer information retrieval by executing a query via ranking a set of search result candidates higher than another set search result candidates based at least in part on the query and determining that a first set of search result candidates are indicative of a sub-accessory to an accessory or an accessory itself.
A communication indicating initiation of a payment transaction by a first device is received. Responsive to the initiation of the payment transaction by the first device, a second device is prompted to complete the payment transaction based on the second device corresponding to a user profile associated with the first device. The payment transaction is completed based on the second device facilitating a payment corresponding to the payment transaction.
A method and a system process a stream of data in parallel across a plurality of nodes. The log processing system has a log module, a query language module, and a query processing module. The log module receives and organizes the stream of data into a sequential and nested data structure. The query language operator module defines operators that operate on the sequential and nested data structure. The query processing module processes in parallel across a plurality of nodes a query based on an operator on the stream of data.
In various example embodiments, a system and method for data mesh-based environmental augmentation are presented. Attribute data associated with a user may be received from a plurality of attribute sources. A portion of the attribute data may include real-time data. A portion of the real-time data indicative of an identity of the user may be identified. The identity of the user may be authenticated with respect to the real-time data by analyzing the identified portion of the real-time data. Based on the authentication of the identity of the user, a user activity being performed by the user may be identified based on the real-time data, and the user activity may be augmented according to a user setting.
H04L 43/04 - Processing captured monitoring data, e.g. for logfile generation
H04L 67/10 - Protocols in which an application is distributed across nodes in the network
H04L 67/1042 - Peer-to-peer [P2P] networks using topology management mechanisms
H04W 4/80 - Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
A server receives an initial query that identifies a first item listed by a first user account and an initial query value for the first item. The server provides the initial query to a first computing device associated with the first user account and receives a first response to the initial query from the first computing device. The first response indicates a rejection of the initial query value. In response to the rejection, the server identifies a second item listed by a second user account. The second item includes a shared attribute with the first item. The server substitutes the initial query with a replacement query that identifies the second item and the initial query value for the first item. The replacement query is provided to a second computing device associated with the second user account.
Apparatus and method for providing contextual recommendations based on user state are disclosed herein. In some embodiments, sensor data corresponding to at least one sensor included in an item worn by a user is received. A user state is determined based on the received sensor data. In response to a state change being satisfied by at least the user state, a recommendation is determined based on the user state and a profile associated with the user. The recommendation may be presented on an electronic mobile device associated with the user.
Aspect pre-selection techniques using machine learning are described. In one example, an artificial assistant system is configured to implement a chat bot. A user then engages in a first natural-language conversation. As part of this first natural-language conversation, a communication is generated by the chat bot to prompt the user to specify an aspect of a category that is a subject of a first natural-language conversation and user data is received in response. Data that describes this first natural-language conversation is used to train a model using machine learning. Data is then received by the chat bot as part of a second natural-language conversation. This data, from the second natural-language conversation, is processed using the model as part of machine learning to generate the second search query to include the aspect of the category automatically and without user intervention.
G06N 3/006 - Artificial life, i.e. computing arrangements simulating life based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
A multimodal embedding modifier generates a modified seed search selection embedding for providing a set of search results. The multimodal embedding modifier enhances the ability and accuracy of identifying a user's true intent when searching the online marketplace. For example, embodiments disclosed herein can allow a user to navigate multiple modalities for an item. In some embodiments, a user may select a search result corresponding to an initial search query, and further modify the selected search result by inputting a modifier (e.g., a textual modifier). The multimodal embedding modifier can be trained using a training dataset including a text embedding, an image embedding, another type of embedding, or a combination thereof.
Techniques are provided for managing media bandwidth usage. In some aspects, a request for an image in a first resolution is received. It is determined that communicating the image in the first resolution violates a network connection state restriction for a network connection with a computing device. Based on determining that communicating the image in the first resolution violates the network connection state restriction, the image in a second resolution that is lower than the first resolution is retrieved. The image in the second resolution can be presented at the computing device.
H04L 67/02 - Protocols based on web technology, e.g. hypertext transfer protocol [HTTP]
H04L 67/125 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks involving control of end-device applications over a network
H04L 67/53 - Network services using third party service providers
H04N 7/173 - Analogue secrecy systems; Analogue subscription systems with two-way working, e.g. subscriber sending a programme selection signal
H04N 21/262 - Content or additional data distribution scheduling, e.g. sending additional data at off-peak times, updating software modules, calculating the carousel transmission frequency, delaying a video stream transmission or generating play-lists
H04N 21/2662 - Controlling the complexity of the video stream, e.g. by scaling the resolution or bitrate of the video stream based on the client capabilities
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/462 - Content or additional data management e.g. creating a master electronic program guide from data received from the Internet and a Head-end or controlling the complexity of a video stream by scaling the resolution or bit-rate based on the client capabi
H04N 21/472 - End-user interface for requesting content, additional data or services; End-user interface for interacting with content, e.g. for content reservation or setting reminders, for requesting event notification or for manipulating displayed content
Example embodiments involve a system and methods for identifying valuable view item pages for search engine optimization. The system and methods provide an improvement over existing systems, which do nothing to identify or select valuable view item pages for use in driving traffic from display sites. The system and methods described herein improve the earlier system by predicting the probability of future traffic for a given product based on a number of product level factors as input variables, and identifying a selection of view item pages corresponding to the products with the probability of the highest future traffic in order to maximize the driving natural search traffic to a linked site of the corresponding view item page.
Feeds in a network-based marketplace are described. The system receives a request, over a network, from a user that is associated with feed selection information, and identifies source feeds based on the feed selection information. The source feeds respectively include a first plurality of content elements. The system generates a presentation feed by retrieving a second plurality of content elements from the source feeds. The generating is performed continuously and in real-time. The system segments the presentation feed into pages and generates interfaces that include a first interface based on the pages. The system communicates the first interface, over the network, to the user, responsive to the receiving of the request.
Example methods and systems are directed to a managed inventory. A database may store information regarding items owned by a user. The information regarding an item may include a quantity owned and one or more triggering events. Based on the occurrence of a triggering event, an order for the item may be placed without user intervention. Data to the database may be provided by one or more sensors. Triggering events may be defined in terms of sensor data. The triggering event may be defined by a user or through machine learning. The order may be placed using a predetermined modality or a dynamically-determined modality based on one or more criteria, such as price, shipping speed, and the urgency of the order.
Systems and methods for generating feedback for a webpage based on visual interactions on the webpage are provided. In example embodiments, a user interface (UI) displaying the webpage is presented. The system receives an indication of a selection of an edit trigger and configures the webpage to receive feedback (e.g., one or more user inputs applied to webpage) from the user in response. The user inputs are received, whereby each user input is associated with an identifier of the webpage and coordinates of a location within the webpage. The system processes the user inputs including generating a feedback preview that displays each of the user inputs organized based on a corresponding feedback type. The feedback preview is displayed to the user for approval. Approval of at least a portion of the feedback on the feedback preview will cause the approved feedback to be transmitted to a corresponding entity.
Disclosed are systems and methods for receiving a plurality of comments at a particular phase of a transaction with a member of a networked system, classifying one or more of the plurality of comments into one of a set of predetermined sentiment classifications, applying a trained machine learning system to select a category from a set of predefined categories for each of the one or more comments, applying a natural language processing module to generate a sub-category for each of the one or more comments, associating the generated sub-categories with their respective categories for the one or more comments, and generating a display of the determined categories for the particular transaction with the generated sub-categories, each generated sub-category being graphically connected to their respective categories.
Technologies are shown for automatic account generation for a transaction between two user devices. In accordance with some aspects, machine readable code is received at a first user device of a first user from a second user device of a second user. The machine readable code is associated with an item token for a transaction between the users. Responsive to receiving the machine readable code: an authentication token is received in response to authenticating the first user, and an account creation request that includes the item token and the authentication token is sent to an intermediary transaction service. The account creation request causes the intermediary transaction service: to generate a first account for the first user using information for the first user obtained using the authentication token, and to facilitate a transaction for the item between the first account and a second account of the second user.
G06F 21/32 - User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
G06Q 20/02 - Payment architectures, schemes or protocols involving a neutral third party, e.g. certification authority, notary or trusted third party [TTP]
G06Q 20/32 - Payment architectures, schemes or protocols characterised by the use of specific devices using wireless devices
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check of credit lines or negative lists
24.
TECHNIQUES FOR GENERATING A THREE DIMENSIONAL MODEL FOR A LISTING
An application server associated with an online marketplace may receive a set of images of an item, spatial information associated with each image of the set of images indicating a relative spatial location to the item for each image, and viewing direction information indicating a viewing direction relative to the item for each image. The application server may then generate a neural radiance field model of the item in a three dimensional space based on the set of images, the spatial information, and the viewing direction information, and may generate a set of spherical harmonics for the neural radiance field model based on predicting one or more spherical harmonic coefficients using the set of images, the spatial information, and the viewing direction information. The application server may then output a three dimensional model of the item generated based on the set of spherical harmonics.
Systems and methods for are provided for predicting impending failure of a database and preemptively initiating mitigating failover actions, for example by shedding connections or redirecting connection requests to an alternate database that can fulfill resources being requested. In an example embodiment, to detect a slow or unstable database, connection wait times are monitored over a rolling window of time intervals, a quantity of intervals in which at least one excessive wait time event occurred are counted during the time window, and if the quantity exceeds a threshold, the database is deemed unavailable, thereby triggering connection adjustments.
The disclosed technologies include a robotic selling assistant that receives an item from a seller, automatically generates a posting describing the item for sale, stores the item until it is sold, and delivers or sends the item out for delivery. The item is placed in a compartment that uses one or more sensors to identify the item, retrieve supplemental information about the item, and take pictures of the item for inclusion in the posting. A seller-supplied description of the item may be verified based on the retrieved supplemental information, preventing mislabeled items from being sold.
Systems and methods change a user interface for the purpose of pairing a shipping container with an item that is intended to be shipped in the shipping container. Example embodiments include a machine-implemented method for accessing a shipping request, detecting a radio signal from a candidate container using a radio receiver, detecting an impact between a pairing device and a query container using an accelerometer, determining that the query container is the candidate container, and generating a shipping record that correlates the shipping container and the item. The device can further determine that the query container is the candidate container based on the signal strength and change in signal strength of one or more signals. The device can further detect an impact between the pairing device and the query container by ranking one or more sets of acceleration data collected by the accelerometer.
H04B 1/38 - Transceivers, i.e. devices in which transmitter and receiver form a structural unit and in which at least one part is used for functions of transmitting and receiving
A method of training a machine learning model to determine an item margin is provided. The method includes monitoring a first value for a first item having attributes and monitoring a first value for a second type of item having attributes where an attribute of the first attributes is the same as an attribute of the second attributes. The method also includes determining a first margin based on the first values. The first attributes, the second attributes, and the first margin are input as training data for the machine learning model where the machine learning model is trained with the training data. The monitoring operations for the first item and the second item are repeated to obtain a second value for the first and second items. Furthermore, the trained machine learning model is applied to the second values to determine a second margin.
In various example embodiments, a system and method for dynamically generating user interface elements and associated values are presented. An item listing and profile data are accessed. A set of user interface elements are dynamically generated based on the item listing and the profile data, with each user interface element configured to perform an action on the item listing. A set of values are dynamically determined, with each value being associated with a user interface element of the set of user interface elements. The set of user interface elements are then caused to be presented within the item listing.
Described are computing systems and methods configured to detect a small, but meaningful, anomaly within one or more metrics associated with a platform. The system displays visuals of the metrics so that a user monitoring the platform can effectively notice a problem associated with the anomaly and take appropriate action to remediate the problem. An operational visual includes a radar-based visual with a heatmap arranging metrics, and a node representing a state of the metrics. Moreover, the system uses an ensemble of unsupervised machine learning algorithms for multi-dimensional clustering of hundreds of thousands of monitored metrics. Via the visuals and the implementation of the machine learning algorithms, the described techniques provide an improved way of representing and simulating many metrics being monitored for a platform. Moreover, the techniques are configured to expose actionable and useful information associated with the platform in a manner that can be effectively interpreted.
G06F 3/04842 - Selection of displayed objects or displayed text elements
G06N 3/04 - Architecture, e.g. interconnection topology
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]
A set of images is accessed from a server. The set is analyzed to identify objects in each image using object recognition algorithms. A primary image that includes more of the identified objects than any of the other images of the set is determined. For each of the identified objects in the primary image, a secondary image that includes the identified object and has a higher magnification than the primary image is determined. Links are inserted into the primary image at locations including an identified object that is also in a secondary image. The primary image is displayed and, upon receiving a selection of one of the links, the secondary image that includes the identified object at the location of the selected link is displayed. The set of images is ordered based on relative positions of the identified objects in each image and then linked together based on the ordering.
Software is increasingly being developed as a collection of loosely coupled applications. Loosely coupled applications exchange data by publishing data to and retrieving data from a data store, such as a database, a file located on a storage cluster, etc. Data produced by one application and consumed by another is referred to as a data dependency. In some embodiments, an application's data dependencies are identified by analyzing cached query plans associated with the application. Query plans include a hierarchical representation of a query, where non-leaf nodes represent commands and leaf nodes identify data dependencies. An application's data dependencies are identified by traversing the hierarchical representation of the query. Data dependencies consumed by the application are identified by finding leaf nodes that descend from a read command, while data dependencies produced by the application are identified by finding leaf nodes that descend from a write command.
Computer information retrieval by automatically marking at least a first item listing, of a first set of item listings, as a candidate for removal as a search result for a query. Such automatic marking occurs in response to receiving an indication that a selection has been made at a computing device, where the selection is at least partially indicative of the user requesting removal, from a set of search results, of a first item listing based on a particular attribute value associated with the first item listing.
A process for linking related images and videos is disclosed. The process can include receiving listing information including the images and the video, processing the images using an image processor to determine one or more image descriptors, processing the video using a video processor to determine video descriptors, comparing the image descriptors to the video descriptors, calculating a similarity value for each of the image descriptors in relation to each of the video descriptors, and linking the videos and the images based upon the calculated similarity value. The method can also include causing the display of a user interface including a video linking user interface element operable to cause playback of a relevant portion of the video linked with the displayed image and an image linking user interface element operable to cause display of a relevant image linked with a portion of the video playback.
G06F 16/41 - Indexing; Data structures therefor; Storage structures
G06V 20/40 - Scenes; Scene-specific elements in video content
G06F 18/21 - Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
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
G06Q 30/02 - Marketing; Price estimation or determination; Fundraising
The disclosed technologies include receiving a request from a second computing device to verify ownership of a blockchain address. A challenge content is generated and sent to the requestor. A signature is received comprising a hash of the challenge content generated using a private key. A public key corresponding to the private key is obtained, and the signature is validated using the public key. In response to validating the signature, a characteristic is associated with a user associated with the blockchain address.
G06Q 10/0835 - Relationships between shipper or supplier and carriers
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
G06K 19/07 - Record carriers with conductive marks, printed circuits or semiconductor circuit elements, e.g. credit or identity cards with integrated circuit chips
G06Q 50/28 - Logistics, e.g. warehousing, loading, distribution or shipping
G06K 7/14 - Methods or arrangements for sensing record carriers by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
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
G06F 16/955 - Retrieval from the web using information identifiers, e.g. uniform resource locators [URL]
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check of credit lines or negative lists
Systems and methods for multi-directional visual browsing on an electronic device are described. In example embodiments, a primary result and a peripheral result are determined. A display layout based on attributes associated with the primary result and the peripheral result is generated. The display layout is then formatted into instructions, which will cause a device to render the display layout. The instructions are transmitted to the client device.
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
G06F 3/04842 - Selection of displayed objects or displayed text elements
G06F 3/04815 - Interaction with a metaphor-based environment or interaction object displayed as three-dimensional, e.g. changing the user viewpoint with respect to the environment or object
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
37.
MATCHING INFLUENCERS WITH CATEGORIZED ITEMS USING MULTIMODAL MACHINE LEARNING
Various embodiments include systems, methods, and non-transitory computer-readable media for identifying and matching influencers with categorized products using multimodal machine learning technologies. Consistent with these embodiments, a method includes identifying an influencer based on a set of criteria; determining a first attribute of the influencer based on context data associated with the influencer; identifying a second attribute of an item; generating a first vector that represents the first attribute of the influencer and a second vector that represents the second attribute of the item; generating a similarity score that represents a degree of similarity between the influencer and the item based on the first vector and the second vector; and causing display of the similarity score in a user interface of a device.
In various example embodiments, a system and method for data mesh-based environmental augmentation are presented. Attribute data associated with a user may be received from a plurality of attribute sources. A portion of the attribute data may include real-time data. A portion of the real-time data indicative of an identity of the user may be identified. The identity of the user may be authenticated with respect to the real-time data by analyzing the identified portion of the real-time data. Based on the authentication of the identity of the user, a user activity being performed by the user may be identified based on the real-time data, and the user activity may be augmented according to a user setting.
H04W 4/80 - Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
H04L 67/1042 - Peer-to-peer [P2P] networks using topology management mechanisms
H04W 84/18 - Self-organising networks, e.g. ad hoc networks or sensor networks
H04L 101/69 - Types of network addresses using geographic information, e.g. room number
39.
METHODS AND APPARATUS FOR DETECTION OF SPAM PUBLICATION
In various example embodiments, a system and method for determining a spam publication using a spam detection system are presented. The spam detection system receives, from a device, an image of an item and an item attribute for the item. Additionally, the spam detection system extracts an image attribute based on the received image, and compares the item attribute and the image attribute. Moreover, the spam detection system calculates a confidence score based on the comparison. Furthermore, the spam detection system determines that the item attribute is incorrect based on the confidence score transgressing a predetermined threshold. In response to the determination that the item attribute is incorrect, the spam detection system causes presentation, on a display of the device, of a notification.
G06V 10/56 - Extraction of image or video features relating to colour
G06V 10/46 - Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features
G06F 18/2413 - Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
Augmented reality, computer vision, and digital ticketing system techniques are described that employ a location determination system. In one example, the location determination system is configured to receiving at least one digital image as part of a live camera feed, identify an object included in the at least one digital image using object recognition, determine a location of the object in relation to a digital map of a physical environment, generate augmented reality digital content indicating the determined location in relation to the digital map, and render the augmented reality digital content as part of the live camera feed for display by a display device.
G06Q 10/02 - Reservations, e.g. for tickets, services or events
G06F 16/583 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
G01C 21/00 - Navigation; Navigational instruments not provided for in groups
G01C 21/36 - Input/output arrangements for on-board computers
G06V 20/62 - Text, e.g. of license plates, overlay texts or captions on TV images
41.
Physical Object Boundary Detection Techniques and Systems
Physical object boundary detection techniques and systems are described. In one example, an augmented reality module generates three dimensional point cloud data. This data describes depths at respective points within a physical environment that includes the physical object. A physical object boundary detection module is then employed to filter the point cloud data by removing points that correspond to a ground plane. The module then performs a nearest neighbor search to locate a subset of the points within the filtered point cloud data that correspond to the physical object. Based on this subset, the module projects the subset of points onto the ground plane to generate a two-dimensional boundary. The two-dimensional boundary is then extruded based on a height determined from a point having a maximum distance from the ground plane from the filtered cloud point data.
Technologies are shown for session centric access control of a remote connection. A request for a remote connection is received from a client. A container is created for the remote connection, and an identifier for each of one or more endpoints authorized for the remote connection are stored in the container. A secure shell is initiated for the remote connection. Access is provided to the first endpoint from the one or more endpoints via the secure shell based on a first identifier for the first endpoint being stored in the container.
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
G06F 21/45 - Structures or tools for the administration of authentication
43.
SYSTEMS AND METHODS FOR CUSTOMIZING ELECTRONIC MARKETPLACE APPLICATIONS
An application configured to be dynamically and/or incrementally updated to tailor capabilities of the application to areas of interest of a user is disclosed. The application receives one or more task-specific modules for enhancing a task-specific capability of the application. The one or more task-specific modules are identified from among a plurality of task-specific modules, based on user data indicative of interaction of the user with an electronic marketplace. The one or more task-specific modules are used to update a general module configured to implement the task-specific capability of the application to create a customized application. The customized application is used to perform a task-specific operation based on an input provided by the user, and a result of the task-specific operation to be presented to the user.
Systems and methods for neural machine translation are provided. In one example, a neural machine translation system translates text and comprises processors and a memory storing instructions that, when executed by at least one processor among the processors, cause the system to perform operations comprising, at least, obtaining a text as an input to a neural network system, supplementing the input text with meta information as an extra input to the neural network system, and delivering an output of the neural network system to a user as a translation of the input text, leveraging the meta information for translation.
Systems, methods, and computer program products for identifying a relevant candidate product in an electronic marketplace. Embodiments perform a visual similarity comparison between candidate product image visual content and input query image visual content, process formal and informal natural language user inputs, and coordinate aggregated past user interactions with the marketplace stored in a knowledge graph. Visually similar items and their corresponding product categories, aspects, and aspect values can determine suggested candidate products without discernible delay during a multi-turn user dialog. The user can then refine the search for the most relevant items available for purchase by providing responses to machine-generated prompts that are based on the initial search results from visual, voice, and/or text inputs. An intelligent online personal assistant can thus guide a user to the most relevant candidate product more efficiently than existing search tools.
G06F 16/583 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
Technologies are shown for function level permissions control for smart contract execution to implement permissions policy on a blockchain. Permissions control rules control function calls at a system level utilizing function boundary detection instrumentation in a kernel that executes smart contracts. The detection instrumentation generates a call stack that represents a chain of function calls in the kernel for a smart contract. The permissions control rules are applied to the call stack to implement permissions control policy. Permissions control rules can use dynamic state data in the function call chain. If the dynamic state data observed in function call chains does not meet the requirements defined in the permissions control rules, then the function call can be blocked from executing or completing execution. The permissions control rules can be generated for a variety of different entities, such as a domain, user or resource.
G06F 21/54 - Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems during program execution, e.g. stack integrity, buffer overflow or preventing unwanted data erasure by adding security routines or objects to programs
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
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check of credit lines or negative lists
G06Q 20/36 - Payment architectures, schemes or protocols characterised by the use of specific devices using electronic wallets or electronic money safes
Disclosed are a system comprising a computer-readable storage medium storing at least one program, and a computer-implemented method for event messaging over a network. A subscription interface receives data indicative of a subscription request for sessionized data. An allocation module allocates a sessionizer bank linked to the subscription request. A messaging interface module provisions identifiers linked to the respective processing engines of the sessionizer bank. The messaging interface module registers the allocated sessionizer bank as available to process event messages matching the subscription request by providing the provisioned identifiers. The messaging interface module receives event messages from a producer device linked by a collection server to a selected one of the processing engines of the sessionizer bank. The selected one of the processing engine processes the received event messages in accordance with session rule data linked to the subscription request to generate sessionized data.
G06F 15/17 - Interprocessor communication using an input/output type connection, e.g. channel, I/O port
H04L 67/10 - Protocols in which an application is distributed across nodes in the network
G06F 15/16 - Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
G06Q 10/101 - Collaborative creation, e.g. joint development of products or services
One or more of the systems, apparatuses, or methods discussed herein can include a quality score for a plurality of item listings or collections of item listings. Data sparseness can be avoided, as the quality score is based on inherent properties of the listing. An item listing can be recommended to a user based on the quality score. In one or more embodiments, a method can include determining a plurality of quality scores including a quality score for each of a plurality of item listings or a plurality of collections of item listings, the quality scores determined independent of a user's attributes and independent of the user's contextual information, the contextual information corresponding to details of the user's access to a website, and recommending an item listing or collection of item listings to a user based on the quality scores and the contextual information.
Systems, methods, and computer-storage media provide content item retrieval that is personalized and time aware for a user. Interaction tracking is performed to identify content items with which the user has interacted and time data indicative of when the user interacted with each content item. A machine learning model is trained using the content items and the time data associated with each content item. Once trained, the machine learning model is used to generate a relevance score for each of a number of target content items. At least a portion of the target content items are provided for presentation to the user based on the relevance scores.
Technologies are shown for storing data from a data object in a distributed application architecture and reassembling the data object from the stored data. A first set of data from the data object is stored on a distributed file system, and a second set of data from the data object is stored on a blockchain. In response to a request for the data object, a script from the blockchain is executed to generate a reassembled data object by: obtaining, from the blockchain, metadata to reassemble the data object, obtaining the second set of data from the blockchain and the first set of data from the distributed file system, and generating the reassembled data object using the first set of data and the second set of data based on the metadata.
G06T 19/00 - Manipulating 3D models or images for computer graphics
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
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 10/22 - Image preprocessing by selection of a specific region containing or referencing a pattern; Locating or processing of specific regions to guide the detection or recognition
G06V 10/98 - Detection or correction of errors, e.g. by rescanning the pattern or by human intervention; Evaluation of the quality of the acquired patterns
G06V 20/20 - Scenes; Scene-specific elements in augmented reality scenes
A tax category prediction model, which is trained using a tax category prediction dataset, provides a tax category prediction for an item having an item listing. The tax category prediction model enhances the ability and accuracy of identifying a tax category associated with an item for sale via the online marketplace (e.g., identifying the tax category before the item is offered for sale via the online marketplace). The tax category prediction dataset is generated based on one or more of a text embedding, an image embedding, another type of embedding, or a combination thereof. The text embedding may be identified by applying a natural language processing model to a text string of the item listing. The natural language processing model may comprise bidirectional encoder representations from transformers (BERT).
Technologies are shown for controlling a transaction on a blockchain. A first block is created on a blockchain for a transaction involving a seller entity associated with a first key, a buyer entity associated with a second key, and an intermediary entity associated with a third key. Funds for the transaction are associated with the first block. A second block storing refund code is created and linked to the first block. The refund code is executable to refund the funds when a seller digital signature using the first key and/or an intermediary digital signature using the third key are received. A third block storing payment code is created and linked to the first block. The payment code is executable to transfer the funds when a buyer digital signature using the second key and/or an intermediary digital signature using the third key are received.
Methods for face detection to address privacy in publishing image datasets is described. A method may include face classification in an online marketplace. A server system may receive, from a seller user device, a listing including an image for the online marketplace. The server system may classify, by at least one processor that implement a distribution-balance trained machine learning model, each human face candidate within the image as being one of a private human face or a non-private human face. The server system may receive, from a buyer user device, a search query that is mapped to the listing in the online marketplace. The server system may transmit, to the buyer user device, a query response including the listing that includes the image determined to not include any private human faces or obscures any private human faces within the image based on the classifying.
Methods, systems, and computer programs are presented for adding new features to a network service. A method includes receiving an image depicting an object of interest. A category set is determined for the object of interest and an image signature is generated for the image. Using the category set and the image signature, the method identifies a set of publications within a publication database and assigns a rank to each publication. The method causes presentation of the ranked list of publications at a computing device from which the image was received.
G06F 16/532 - Query formulation, e.g. graphical querying
G06F 16/50 - Information retrieval; Database structures therefor; File system structures therefor of still image data
G06F 16/583 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
G06N 3/084 - Backpropagation, e.g. using gradient descent
G06V 10/46 - Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features
G06F 18/2415 - Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on parametric or probabilistic models, e.g. based on likelihood ratio or false acceptance rate versus a false rejection rate
G06F 18/2113 - Selection of the most significant subset of features by ranking or filtering the set of features, e.g. using a measure of variance or of feature cross-correlation
G06F 18/2411 - Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on the proximity to a decision surface, e.g. support vector machines
G06N 3/044 - Recurrent networks, e.g. Hopfield networks
Systems and methods are directed to using counterfactual machine-learning analysis to improve a probability of transaction conversion. The system trains a model with training data extracted from past transactions, whereby the model determines a probability for transaction conversion based in part on user account behavior. The system monitors the user account behavior associated with a potential buyer including tracking a first action performed involving an item of a listing. A user attribute associated with the user account and an item attribute associated with the item are determined. Based on the first action, the probability is determined by applying the user attribute, the item attribute, and the user account behavior to the model. Based on the probability being less than a conversion threshold, counterfactual analysis is performed to identify a change associated with the item that results in the probability exceeding the conversion threshold. The change may be automatically implemented.
Methods, systems, and articles of manufacture, including computer program products, are provided for image cleanup. In some embodiments, there is provide a method which may include subsampling a first image to a first level image of a multiscale transform; performing, based on a machine learning model, an identification of a foreground portion of the first level image and a background portion of the first level image; generating, based on the identification of the foreground portion and the background portion, a first mask; upscaling the first mask to a resolution corresponding to the first image depicting the foreground item; applying the upscaled first mask to the first image to form a second image depicting the foreground item; and providing the second image depicting the foreground item to a publication system. Related systems and articles of manufacture, including computer program products, are also provided.
Various embodiments use a neural network to analyze images for aspects that characterize the images, to present locations of those aspects on the images, and, additionally, to permit a user to interact with those locations on the images. For example, a user may interact with a visual cue over one of those locations to modify, refine, or filter the results of a visual search, performed on a publication corpus, that uses an input image (e.g., one captured using a mobile device) as a search query.
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
G06V 20/20 - Scenes; Scene-specific elements in augmented reality scenes
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06F 18/2413 - Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
G06N 3/044 - Recurrent networks, e.g. Hopfield networks
G06N 7/01 - Probabilistic graphical models, e.g. probabilistic networks
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
60.
Adaptive Timing Prediction For Updating Information
Technologies are disclosed herein for distributing information. The disclosed technologies determine an application element configured to receive information that is updated at a variable rate, the information pertaining to an object. Feature data is received that is associated with the object and data associated with use of the application element. The feature data includes a time horizon for the object and supplemental information associated with the object. Based on the feature data and the data associated with use of the application element, a first rate is predicted for sending the information about the object to the application element. The information is sent to the application element at the first rate.
Example methods and systems are directed to a managed inventory. A database may store information regarding items owned by a user. The information regarding an item may include a quantity owned and one or more triggering events. Based on the occurrence of a triggering event, an order for the item may be placed without user intervention. Data to the database may be provided by one or more sensors. Triggering events may be defined in terms of sensor data. The triggering event may be defined by a user or through machine learning. The order may be placed using a predetermined modality or a dynamically-determined modality based on one or more criteria, such as price, shipping speed, and the urgency of the order.
A search system performs item retrieval using search query categorization that matches query intent. Category embeddings are generated for categories based on hierarchical data and search information. For instance, the category embeddings can be generated using information regarding hierarchical relationships between the categories, co-occurring relationships between categories identified from search information, and initial embeddings that encode query-related information for each category. Category clusters can be formed using the category embeddings. When a search query is received, one or more categories are identified from a category cluster and used for selecting search results for the search query.
An experimentation platform controls testing of features by an application server. Based on a user identifier, the experimentation platform determines which feature should be provided, and the application server provides the corresponding version of a user interface. If the user behavior data shows that using a tested feature results in an improvement, the tested feature will be adopted. To determine whether or not an improvement is observed, a statistically significant amount of data is gathered. The experimentation platform gathers data regarding user behavior for the feature versions and, in response, adjusts the frequency at which each version is served. Providing the proposed version to an increased percentage of users decreases the total number of page serves required to gather statistically significant data. The experimentation platform may provide an updated projected time to completion of testing based on the changed percentage of users receiving the proposed version.
A system and method for a trusted fulfillment agent network system is described. A network of trusted fulfillment agents is generated for a seller in an online marketplace. A transaction between a buyer and the seller corresponding to a listing of the seller in the online marketplace is accessed. A request is generated to the network of trusted fulfillment agents of the seller to fulfill a shipment of an item from the listing to the buyer on behalf of the seller.
Methods and systems for protecting seller privacy during an ecommerce transaction are disclosed. In one aspect, a method includes, receiving, via an online listing configuration interface for a first session, one or more candidate pick up times and specific pick up locations for an item, determining a generalized version of the one or more specific pick up locations, displaying, via a second session, an online listing for the item, displaying, via the second session, the one or more candidate pick up times and the generalized versions of the one or more specific pick up locations, receiving, via the second session, a selection of one of the candidate pick up times and one of the generalized versions of one of the specific pick up locations, in response to receiving payment for the item, displaying a specific pick up location corresponding to the selected one generalized version.
Systems, methods, and computer program products for identifying a candidate product in an electronic marketplace based on a visual comparison between candidate product image visual content and input query image visual content. Embodiments generate and store descriptive image signatures from candidate product images or selected portions of such images. A subsequently calculated visual similarity measure serves as a visual search result score for the candidate product in comparison to an input query image. Any number of images of any number of candidate products may be analyzed, such as for items available for sale in an online marketplace. Image analysis results are stored in a database and made available for subsequent automated on-demand visual comparisons to an input query image. The embodiments enable substantially real time visual based product searching of a potentially vast catalog of items.
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06F 16/583 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
G06F 16/51 - Indexing; Data structures therefor; Storage structures
G06F 16/2457 - Query processing with adaptation to user needs
G06V 10/75 - Image or video pattern matching; Proximity measures in feature spaces using context analysis; Selection of dictionaries
G06F 18/2411 - Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on the proximity to a decision surface, e.g. support vector machines
A recommendation system leverages multi-target search to provide item listing recommendations and/or query suggestions. For a given input image with multiple objects, multi-target search uses object detection to detect each object, and stores complementary object data associating each object from the image. Additionally, a search of an item listing datastore is performed using each object from the image as a search query. Based on item listings returned as search results, complementary item listings data associating item listings is stored. In some configurations, the complementary item listings data is also used to train a machine learning model to predict complementary item listings for a given item listing. When an input item listing is received, item listing recommendations and/or query suggestions are determined for the input item listing using the complementary object data, the complementary item listing data, and/or the machine learning model.
A computer-implemented method includes determining a set of target listings, retrieving a seed image associated with the seed listing, the seed listing is categorized within a first item category, and generating a seed item feature vector for the seed image using a convolutional neural network (CNN) trained with images of items. The method also includes identifying a plurality of feature vectors associated with the first item category, comparing the seed item feature vector to the plurality of feature vectors using a k-nearest neighbors (kNN) algorithm, and generating a set of nearest neighbor listings to the seed listing. The method further includes storing the set of nearest neighbor listings as associated with the seed listing, selecting one or more nearest neighbor listings from the set of nearest neighbors, and presenting the one or more nearest neighbor listings as a recommendation to a user of the online e-commerce system.
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
G06F 18/2413 - Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
69.
GENERATING KEYWORDS BY ASSOCIATIVE CONTEXT WITH INPUT WORDS
Systems and methods are provided for accessing a plurality of inventory item listings accessible over a network, wherein each of the plurality of inventory item listings includes one or more text strings, and creating inventory word vectors for at least some of the text strings of the plurality of inventory item listings. The systems and methods further provide for receiving a user input including an input word, wherein the user input is input by a user to access a primary media content, creating an input word vector for the input word, calculating cosine similarities between the input word vector and the inventory word vectors, and analyzing the calculated cosine similarities to determine one or more keywords from the one or more text strings, wherein the one or more keywords are from the text strings having inventory word vectors with the highest cosine similarities to the input word vector.
Technologies described reduce the amount of time between requesting content and receiving the requested content. In some embodiments, a client provides a search query. A search result page is generated and, prior to returning the search result page to the client, some or all of the search results are asynchronously pre-fetched and cached. The search query can include custom parameters that are also included in the pre-fetch requests. Web addresses in the search results page can be modified to indicate whether a prefetch operation was initiated. Once a user activates one of the search results, the responding web server uses the cached data while generating a response.
A system and method of providing user customizable web advertisements are disclosed. In some embodiments, the system may include a non-transitory, computer-readable medium storing computer-executable instructions and one or more processors. When the one or more processors execute the computer-executable instructions, the processors may be configured to receive a customizable advertisement, the customizable advertisement having at least one customizable portion. When a customizable portion is selected, the one or more processors may display a plurality of customization options for the at least one customizable portion. The one or more processors may be further configured to receive a selection of a customization option from the plurality of customization options. The one or more processors may then apply the selected customization option to the customizable portion of the customizable advertisement. Afterwards, the one or more processors may then display the customizable advertisement with the selected customization option.
Systems and methods for processing webpage calls via multiple module responses are described. A system may receive, from a client device, a first call for module data associated with a set of webpage modules for presentation in a webpage. The system may subsequently transmit, to the client device based on receiving the first call, a first response including first module data associated with a first subset of the set of webpage modules. The first response may additionally include a token identifying the webpage. The server may additionally transmit, to the client device based on transmitting the first response, a second response including the token identifying the webpage and second module data associated with a second subset of the set of webpage modules that differs from the first subset of the set of webpage modules.
A system and method of displaying complementary content on one or more linked machines are disclosed. In some embodiments, the system and method may include a non-transitory, computer-readable medium storing computer-executable instructions and one or more processors in communication with the non-transitory, computer readable medium. When the computer-executable instructions are executed, the one or more processors may be configured to receive a linking instruction to link a display of second content of a website on a second machine to a selection of a portion of first content of the web site by a first machine, cause a display of the first content on the first machine, receive the selection of the portion of the first content displayed on the first machine, and based on the portion of the first content being selected, cause the display of the second content on the second machine based on the linking instruction.
In an example embodiment, an item listing process is run in an item listing application. Upon reaching a specified point in the item listing process, a camera application on the user device is triggered (or the camera directly accessed by the item listing application) to enable a user to capture images using the camera, wherein the triggering includes providing an overlay informing the user as to an angle at which to capture images from the camera.
Technologies are shown for generating process flow graphs from system trace data that involve obtaining raw distributed trace data for a system, aggregating the raw distributed trace data into aggregated distributed trace data, generating a plurality of process flow graphs from the aggregated distributed trace data, and storing the plurality of process flow graphs in a graphical store. A first critical path can be determined from the plurality of process flow graphs based on an infrastructure design for the system and a process flow graph corresponding to the first critical path provided for graphical display. Certain examples can determine a second critical path involving a selected element of the first critical path and provide the process flow graph for the second critical path for display. Some examples pre-process the aggregated distributed trace data to repair incorrect traces. Other examples merge included process flow graphs into longer graphs.
A search system performs item searches using morphed images. A morphed image is generated using a generative model operating on two or more images of objects. A first search is performed on an item database using the morphed image as search input to identify one or more search results, which are provided for presentation. A selection of a first search result from the one or more search results is received. A further morphed image is generated using the generative model operating on an image corresponding to the first search result. A second search is performed on the item database using the further morphed image as search input to identify one or more further search results, which are provided for presentation.
A system may receive, via a user interface associated with an online marketplace, a request to generate the listing for the item, the request including a natural language text input as a title for the listing. The system may generate, based on inputting the natural language text to a transformer-based machine learning model, a predicted value for an item description attribute of the item. In some examples, a value of the item description attribute may be unspecified in the natural language text and may describe a feature associated with the item as produced. The system may then cause presentation, via the user interface associated with the online marketplace, of the listing including the predicted value for the item description attribute.
Fingerprinting physical items to mint NFTs is described. One or more features of a physical item are captured using a fingerprint capture system of a client device, and a fingerprint of the physical item is generated using the captured features of the physical item. The fingerprint of the physical item is provided to an authentication service to verify that the physical item corresponds to an authentic physical item by matching the fingerprint of the physical item to distinguishing features of the authentic physical item. Responsive to verification by the authentication service, a digital twin NFT is minted on a blockchain using the matched fingerprint. A combined listing for the physical item and the digital twin NET is then generated on a listing platform.
Extended reality auction techniques are described that support conducting live auctions in an extended reality environment, such as augmented or virtual reality environments. Image data, for instance, is received by a computing device from a first computing device depicting an item for auction. An extended reality auction system initiates an auction for the item based on identifying that at least part of the item is in the image data. The image data is provided to a second computing device for display in the extended reality environment during the auction. Responsive to determining that a criterion of the auction is not satisfied by the image data, remedial action is initiated by the extended reality auction system.
G06T 19/00 - Manipulating 3D models or images for computer graphics
H04L 67/131 - Protocols for games, networked simulations or virtual reality
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
80.
TRANSACTION RISK ASSESSMENT USING MACHINE-TRAINED MODELS
Systems and methods are directed to assessing risk and triggering a mitigation action prior to executing an offer based on a level of risk. Risk models are trained with data extracted from past transactions, whereby the risk models are configured to determine levels of risk for potential transactions. A request to make an offer on a listing representing an item is received. In response, the system identifies one or more account attributes associated with the user account and determines a level of risk by applying the one or more account attributes to one or more of the risk models. If the level of risk transgresses a threshold, the system triggers the automatic payment flow prior to executing the offer, which includes causing display of an information request user interface through which payment and shipping information is received. Responsive to receiving the payment and shipping information, the offer is executed.
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check of credit lines or negative lists
81.
Proactive Re-Routing Of Vehicles Using Passive Monitoring Of Occupant Frustration Level
Aspects of the present disclosure include a navigation system and computer-implemented methods for proactively re-routing vehicles based on an analysis of input component data obtained from the navigation-enabled devices. The navigation system scores the input component data to obtain a measure of frustration (e.g., a feeling of being upset or annoyed) of the user of the navigation-enabled device. The navigation system may provide a detour suggestion for display on the navigation-enabled device to persuade the user of the device to direct their vehicle to depart from its current location or route in an effort to remove the vehicle from traffic, and thereby reduce the frustration level of the user. The detour suggestion may include an alternative route to the original destination, or an alternative destination.
Technologies are shown for content distribution on a blockchain. An access request is received for digital content owned by a first entity and associated with one or more blocks of a blockchain. The access request is associated with a second entity. A current use condition associated with the second entity is verified to satisfy a use requirement conditions attribute defined by at least one of the one or more blocks of the blockchain. Responsive to verifying the current use condition satisfies the use requirement conditions attribute, the second entity is provided access to the digital content.
G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
H04L 9/30 - Public key, i.e. encryption algorithm being computationally infeasible to invert and users' encryption keys not requiring secrecy
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
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
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check of credit lines or negative lists
G06F 21/30 - Authentication, i.e. establishing the identity or authorisation of security principals
H04L 67/52 - Network services specially adapted for the location of the user terminal
H04L 9/00 - Arrangements for secret or secure communications; Network security protocols
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
G06F 21/64 - Protecting data integrity, e.g. using checksums, certificates or signatures
83.
THIRD-PARTY APPLICATION RISK ASSESSMENT IN AN AUTHORIZATION SERVICE
Risk assessment in an authentication service is performed where an authorization request is received from a third-party application. Risk assessment policies for the authorization request are determined based on a class of the third-party application. The risk assessment policies are applied to the authorization request to determine an action to be performed for the authorization request, such as sending an authorization message in response to the authorization request or taking a remedial action (e.g., suspending the application, limiting the available actions, or sending a notification to a trusted security application).
Systems and methods are disclosed to provide flaw accentuation to an image in an e-commerce online marketplace. In some embodiments, a method may include receiving at an online marketplace, from a seller through the Internet, an image of an item being listed for sale at the online marketplace and text related to the item being listed for sale; determining that the item includes a flaw based on the text related to the item being listed for sale or the image of the item; creating a flaw accentuation to the image; and creating a listing in the online marketplace for the item that includes the image and the flaw accentuation to the image.
In example embodiments, a system and method for providing item notifications is provided. A networked system receives, from a device of a user, a selection of an item from a list for monitoring. The network system also receives, from the device of the user, a condition that triggers the reporting of news for the selected item. The network system monitors for news for the selected item. A determination is made as to whether the condition that triggers the reporting of the news is satisfied. In response to determining that the condition that triggers the reporting of the news is satisfied, the networked system transmits a notification to the user indicating the news for the selected item.
G06F 16/583 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
G06Q 10/08 - Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
Technologies are shown for trust delegation that involve receiving a first request from a subject client and responding by sending a first token having first permissions to the subject client. A second request from a first partner actor is received that includes the first token, and in response, the first partner actor is linked to the subject client in a trust stack and a second token is sent to the first actor with second permissions, the second token identifying the subject client and the first partner actor. A third request from a second partner actor is received that includes the second token, and in response, the second partner actor is linked to the first partner actor in the trust stack and a third token is sent to the second partner actor with third permissions, the third token identifying the first partner actor and the second partner actor.
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
Disclosed are systems, methods, and non-transitory computer-readable media for message timing optimization. A message timing optimization system determines optimized times to transmit messages to users based on historical transaction data. For example, the message timing optimization system may determine an optimal time to transmit a recommendation message to a user to perform a subsequent, such as repurchasing an item, refreshing a password, and the like. The message timing optimization system uses historical transaction data describing previous transactions performed by the user and/or other users to determine probability values indicating the likelihood that a user will perform a subsequent action at various time periods after the user performed an initial transaction.
Various examples include systems, methods, and non-transitory computer-readable media for generating shipping option recommendations for listing items. Consistent with these examples, a method includes receiving a request to list a first item. The method further includes determining a characteristic of the first item based on item data. The method further includes identifying a set of transactions corresponding to a number of shipped items that share the characteristic with the first item. The method further includes generating a filtered set of transactions from the set of transactions based on the location data. The method further includes identifying a first shipping option based on the filtered set of transactions and generating a shipping option recommendation based on the identified first shipping option.
A method of displaying a user interface is provided. The method includes retrieving reviews for an item and extracting indicia from the retrieved reviews. A first question is generated based on the extracted indicia. A first interactive user interface is displayed that includes the first question along with an option to provide a response that corresponds to a review of the item. A second question and an answer to the second question are generated based on the response to the first question. A second interactive user interface that includes the second question and the answer to the second question is then displayed.
Technologies are disclosed herein for cross-correlating metrics for anomaly root cause detection. Primary and secondary metrics associated with an anomaly are cross-correlated by first using the derivative of an interpolant of data points of the primary metric to identify a time window for analysis. Impact scores for the secondary metrics can be then be generated by computing the standard deviation of a derivative of data points of the secondary metrics during the identified time window. The impact scores can be utilized to collect data relating to the secondary metrics most likely to have caused the anomaly. Remedial action can then be taken based upon the collected data in order to address the root cause of the anomaly.
Techniques are described, as implemented by computing devices, to control access to transactions through use of tokenized reputation scores. This is performed by leveraging a blockchain such that a tokenized reputation score is generated or calculated based on an amount of reputation tokens associated with a blockchain account address associated with a service provider account, and by making transactional functionality available to the service provider account based on a comparison of a tokenized reputation score affiliated with the service provider account with a threshold score associated with a transaction.
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check of credit lines or negative lists
Example embodiments are directed to systems and method to facilitate omnichannel retailing. A networked system determines a location of the user device within a store and accesses a map of the store. An item from a list of one or more items is identified, whereby the item has a plurality of locations within the store. A first location of the item from the plurality of locations is selected. The networked system causes display, on a user interface on the user device, of the location of the user device and the first location of the item and causes display of a user interface element that is operable to receive user selection of a different location from the plurality of locations. In response to receiving the user selection, the networked system ceases display of the first location on the map and causes display of the different location on the map.
A videoconference system is described that generates a video for a room including multiple videoconference participants and outputs the video as part of the videoconference. The videoconference system is configured to generate the video as including a detailed view of one of the multiple videoconference participants located in the room. To do so, the videoconference system detects user devices located in the room capable of capturing video and determines a position of each user device. The videoconference system then detects a user speaking in the room and determines a position of the active speaker. At least one of the user devices is identified as including a camera oriented for capturing the active speaker. Video content captured by one or more user devices is then processed by the videoconference system to generate a detailed view of the active speaker.
09 - Scientific and electric apparatus and instruments
35 - Advertising and business services
42 - Scientific, technological and industrial services, research and design
Goods & Services
Computer e-commerce software to allow users to conduct electronic business transactions in online marketplaces via a global computer network; Computer database software featuring information in the field of hobbies, collectibles and a wide variety of products; Computer software and software development tools for use in developing further software and software applications in the field of e-commerce; Computer software for processing electronic payments to and from others; Authentication software for controlling access to and communications with computers and computer networks Online trading services, namely, operating online marketplaces for sellers and buyers of goods and services; Online trading services in which sellers post products or services to be offered for sale, and purchasing or bidding is done via the Internet in order to facilitate the sale of goods and services by others via a computer network; Providing evaluative feedback and ratings of sellers' goods and services, the value and prices of sellers' goods and services, buyers' and sellers' performance, delivery, and overall trading experience in connection therewith; Providing a searchable online advertising guide featuring the goods and services of online vendors; Providing a searchable online evaluation database for buyers and sellers; Advertising and advertisement services; Business services in the nature of intellectual property claims management, namely, processing and administration of claims of intellectual property owners against third party sellers; Identification verification services, namely, confirming authenticity of products, producers and sellers for the purposes of helping consumers make informed purchasing decisions Design and development of computer software, software applications, and application programming interfaces; Providing temporary use of on-line, non-downloadable computer software and software development tools for use in developing further software and software applications in the field of e-commerce; Providing temporary use of online, non-downloadable e-commerce software to allow users to conduct electronic business transactions in online marketplaces via a global computer network; Maintenance and updating of computer software for others; Providing a website that gives users the ability to create customized web pages featuring user-defined information in the field of intellectual property rights and intellectual property enforcement policies, in order to assist program participants with inquiries and requests regarding use of intellectual property by others in an online marketplace; Providing temporary use of on-line non-downloadable software for processing electronic payments; Providing temporary use of on-line non-downloadable authentication software for controlling access to and communications with computers and computer networks
Techniques are shown for key management using a traceable key blockchain. A first block corresponding to a cryptographic key is generated on the blockchain, and the first block is securely modified to include metadata describing a key source for the cryptographic key. A second block corresponding to a first key transaction with the cryptographic key is generated on the blockchain, the second block is linked to the first block, and the second block is securely modified to include metadata describing the first key transaction with the cryptographic key.
G06F 21/64 - Protecting data integrity, e.g. using checksums, certificates or signatures
H04L 9/00 - Arrangements for secret or secure communications; Network security protocols
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 9/14 - Arrangements for secret or secure communications; Network security protocols using a plurality of keys or algorithms
H04L 9/30 - Public key, i.e. encryption algorithm being computationally infeasible to invert and users' encryption keys not requiring secrecy
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
96.
Multi-legged network attribution using tracking tokens and attribution stack
Technologies are shown for network attribution tracking for a multi-legged transaction. In accordance with some aspects, a first token is provided to a first partner service. A token request is received from a second partner service, wherein the token request includes the first token. A second token is associated with the first token, and the second token is provided to the second partner service. A transaction is attributed to the first partner service and the second partner service based on the association of the second token with the first token.
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check of credit lines or negative lists
97.
Dynamically Generating Visualization Data Based On Shipping Events
Technologies are described for generating visualizations that graphically represent an item being exposed to extreme environmental conditions while en route to a destination. An exemplary visualization may include a still graphic that shows a symbol of a detected environmental condition positioned adjacent to and/or superimposed over a graphic that represents the item. Another exemplary visualization may include an animation that includes a sequence of frames that, when sequentially displayed at a particular frame rate, animate the item being subjected to the detected environmental condition. Various implementations include receiving measurements of the environmental conditions that the item is exposed to from sensors that are proximate to the item while it is en route to the destination. Then, when thresholds are reached for specific environmental conditions (e.g., temperature, acceleration, etc.), visualizations may be generated that graphically represent the item being exposed to such specific environmental conditions.
G06Q 10/0835 - Relationships between shipper or supplier and carriers
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
G06K 19/07 - Record carriers with conductive marks, printed circuits or semiconductor circuit elements, e.g. credit or identity cards with integrated circuit chips
G06Q 50/28 - Logistics, e.g. warehousing, loading, distribution or shipping
G06K 7/14 - Methods or arrangements for sensing record carriers by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
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
G06F 16/955 - Retrieval from the web using information identifiers, e.g. uniform resource locators [URL]
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check of credit lines or negative lists
A system receives image data associated with an item, where the image data comprising a view of the item from two or more angles; determines physical attributes of the item; generates a base model of the item; samples the base model to generate one or more sampled models, each of the one or more sampled models comprising a subset of the geometric data, the subset of the geometric data determined based on one or more device characteristics of one or more user devices that interface with the system; receives device characteristics of a user device associated with a request from the user device for the item; selects, based on the received device characteristics, a sampled model of the item; and transmits a data object comprising the selected sampled model to the user device to cause the user device to generate a three-dimensional rendering of the item.
A system comprising a computer-readable storage medium storing at least one program, and a computer-implemented method for enhancing and personalizing an interactive marketplace. The systems and methods provided herein may allow a user to receive search results that are tailored to the user's personal preferences based on social and purchasing information known about the user. In addition, the systems and methods provided herein may provide shipping updates to a buyer that include a personalized message based on location information provided by the package being shipped. In addition, the systems and methods provided herein allow merchants to provide incentives and rewards for shoppers by participating in interactive shopping games.
A method for training and selecting machine learning models is provided. Data points associated with an item during a first time period and having a selling time associated with the item are obtained. The data points are provided to first and second machine learning models. Both the first and second machine learning models are trained with the data points. The first machine learning model predicts a first selling time using the data points. The second machine learning model predicts a second selling time using the data points. The first and second machine learning models are updatable with additional data points associated with a second time period. Each of the first selling time and the second selling time are compared with the selling time associated with the item. Based on the comparison, one of the first or second machine learning models is selected to predict selling times of future items.