Two sets of data, each containing property listings, are obtained from two discrete merchant platforms. Each property listing in a set of data of a first merchant is sequentially paired with each of the property listings in a set of data of a second merchant. For each pair, each image of the property listing of the first merchant is compared to each image of the property listing of the second merchant, and images of statistically sufficient similarity are identified. The similarity of images, and in particular, of similar images likely to be rooms of the property, are considered in a determination of whether the product listings of the first and second merchant are for the same cross-listed product.
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 10/02 - Reservations, e.g. for tickets, services or events
A method for depicting location attributes in a map environment. The method includes receiving a request for parameters about a first type of location. The method includes determining a first set of directional arrows, where each directional arrow is associated with a location and has a first set of properties based on the parameters about the first type of location. The method further includes determining a selection of a first directional arrow, which is associated with a first location, from the first set of directional arrows. Modifications to the first set of directional arrows are made based on the selection of the first directional arrow.
A search system that receives and returns results for split stays is described. The search system receives, from a searching end-user, a listing request specifying a multiple-day length of stay parameter. The search system determines that the multiple-day length of stay parameter of the listing request transgresses a minimum length of stay threshold and, in response, generates a combined listing that includes a first listing of the plurality of listings associated with a first portion of the multiple-day length of stay parameter and a second listing of the plurality of listings associated with a second portion of the multiple-day length of stay parameter. The combined listing is presented with one or more other listings of the plurality of listings that match the listing request in a ranked order.
A search system that receives and returns results for split stays is described. The search system receives, from a searching end-user, a listing request specifying a multiple-day length of stay parameter. The search system determines that the multiple-day length of stay parameter of the listing request transgresses a minimum length of stay threshold and, in response, generates a combined listing that includes a first listing of the plurality of listings associated with a first portion of the multiple-day length of stay parameter and a second listing of the plurality of listings associated with a second portion of the multiple-day length of stay parameter. The combined listing is presented with one or more other listings of the plurality of listings that match the listing request in a ranked order.
Systems and methods are provided to generate an access code specific to a user of an online marketplace to use to enter a first accommodation during a first reservation time frame and a second accommodation during a second reservation time frame and to send the access code specific to the user to a computing device at the first accommodation and a computing device at the second accommodation to use to enter the first accommodation during the first reservation time period and the second accommodation during the second reservation time period. The access code is automatically removed from the computing device at the first accommodation and the computing device at the second accommodation at the end of the first reservation time period and at the end of the second reservation time period, respectively.
Two sets of data, each containing property listings, are obtained from two discrete merchant platforms. Each property listing in a set of data of a first merchant is sequentially paired with each of the property listings in a set of data of a second merchant. For each pair, each image of the property listing of the first merchant is compared to each image of the property listing of the second merchant, and images of statistically sufficient similarity are identified. The similarity of images, and in particular, of similar images likely to be rooms of the property, are considered in a determination of whether the product listings of the first and second merchant are for the same cross-listed product.
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
G06V 10/75 - Image or video pattern matching; Proximity measures in feature spaces using context analysis; Selection of dictionaries
G06Q 10/02 - Reservations, e.g. for tickets, services or events
Systems and methods are provided to analyze at least one sensor of a computing device to determine that the computing device is in a substantially flat position on the first surface, activate a camera comprising a depth sensor, and detect a second surface in a camera view of the camera. The computing device further analyzes pixel measurements from the depth sensor in a predefined area of the detected second surface to determine a minimum measurement of all of the pixel measurements in the predefined area of the detected surface, causes display of the minimum measurement from the first surface to the second surface overlaid on an image of the first and second surface in the camera view on a user interface of the computing device, and captures an image of the display.
A presentation service generates an audience interface for an electronic presentation. The audience interface may simulate an in-person presentation, including features such as a central presenter and seat locations for audience members. The audience members may select emotes which may be displayed in the audience interface. The emotes may indicate the audience members' opinion of the content being presented. The presentation service may enable chats between multiple audience members, grouping of audience members private rooms, and other virtual simulations of functions corresponding to in-person presentations.
Highly user-specific data is used to calculate user intent to make a purchase and the value of such a purchase. User activity and information is aggregated, per user, for a set window of time and real-time data on recent site behavior is obtained. Aggregated and/or real-time data is considered by a predictive intent model (calculating the probability that the user will make a purchase) and a predictive value model (calculating the expected revenue such a purchase may generate). Weights, specific to each model, are assigned to predictor features tracked in the aggregated and/or real-time user data. The most highly-weighted features of the intent model relate to users' viewing history, and the most highly-weighted features of the value model relate to price and market. By these means, a user conversion value can be obtained, guiding the application of user acquisition strategies for different home sharing markets.
A user is associated with initial search requests, and results that comprise attribute types indicative of a common relationship with other results. Each result has an attribute parameter for each attribute type. Search interaction data. Search interaction data comprises attribute parameter data and user interaction data for the search results. A machine learning algorithm is trained to analyze the search interaction data to recognize common relationships, and used to detect a common relationship between the respective attribute parameters for one of the attribute types for which the user interest data indicates interest. When a subsequent search request is received from the user, a user interest characteristic is computed for each result, based on similarity between the attribute preference data detected using the machine learning algorithm and the attribute parameter for the attribute type. The search results are presented to the user, sorted according to user interest characteristic.
There is provided a method that includes receiving, from a client device, a search request for a set of listings, the search request including search parameters defining a search query. The method further includes generating a set of listings based on the search query and the search parameters and extracting price-indicative and non-price-indicative features. The method also includes computing a probability of booking and an estimate of quality, by inputting the price-indicative features and non-price-indicative features to trained machine learning models. The trained machine learning models predict (i) an affordability metric based on the price-indicative features and (ii) a quality metric based on the non-price- indicative features, separately. The affordability metric and the quality metric are representative of the probability of booking, and the quality metric is representative of the estimate of quality. The method further includes ranking the set of listings based on the booking probability and the quality estimate.
A server obtains content in a first language and receives a first request from a first client device to view the content, wherein the first client device is associated with a second language selected by a user operating the first client device. In response to receiving the first request, the server determines that the first language is different from the second language and determines that a storage of the server does not include a machine-translated version of the content in the second language. In accordance with these determinations, the server obtains a machine-translated version of the content in the second language and stores the machine-translated version of the content in the second language in the storage for subsequent requests to view the content in the second language.
Highly user-specific data is used to calculate user intent to make a purchase and the value of such a purchase. User activity and information is aggregated, per user, for a set window of time and real-time data on recent site behavior is obtained. Aggregated and/or real-time data is considered by a predictive intent model (calculating the probability that the user will make a purchase) and a predictive value model (calculating the expected revenue such a purchase may generate). Weights, specific to each model, are assigned to predictor features tracked in the aggregated and/or real-time user data. The most highly-weighted features of the intent model relate to users' viewing history, and the most highly-weighted features of the value model relate to price and market. By these means, a user conversion value can be obtained, guiding the application of user acquisition strategies for different home sharing markets.
A presentation service generates an audience interface for an electronic presentation. The audience interface may simulate an in-person presentation, including features such as a central presenter and seat locations for audience members. The audience members may select emotes which may be displayed in the audience interface. The emotes may indicate the audience members' opinion of the content being presented. The presentation service may enable chats between multiple audience members, grouping of audience members private rooms, and other virtual simulations of functions corresponding to in-person presentations.
Systems and methods are provided for receiving a request for services in a given location from a client device operated by a user and generating a set of features based on information included in the request for services in the given location. The systems and methods further provide for analyzing the set of features using a machine learning model to predict whether only services that can be instantly booked should be provided in response to the request for services in the given location, analyzing a prediction output by the machine learning model to determine that only services that can be instantly booked should be provided in response to the request for services in the given location, and generating a list with only services that can be instantly booked.
A text-based real-time communication interface, such as a chatbot, is presented to a user for the exchange of customer support information. A user's freeform text input is analyzed using machine learning algorithms to derive the meaning of the input text as well as to determine the user sentiment expressed therein. These determinations may be further supported by signals extracted from session-based activity, which signals can be used to infer the intended workflow of the user and whether or not that workflow was achieved. The expressed user sentiment is considered along with other historical or session-based user data to generate tailored questions and responses to be delivered in real-time to the user. The responses are displayed to the user along with information that routes the user to a workflow resolution.
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
A preliminary software feature is applied in a testing rollout to a discrete subset of customers. Survey data may be collected from those customers through a variety of sources, such as chatbot text, session workflow, historical user data, social media data, email survey data, user profile data, messaging threads, and the like. This survey data is analyzed using machine learning algorithms to derive the meaning of input text as well as to determine the user sentiment expressed therein. The outputs of this analysis are normalized across sources and aggregated at a feature-level to generate overall metrics of customer satisfaction with the feature. A holistic analysis is performed on this customer sentiment data to obtain an aggregate or combined user satisfaction score. This score is applied against a set of guardrails to determine whether to ship the feature to a broader customer base.
A flexible listings search system can receive and return results for flexible listing searches. For example, the system can perform micro-flexible searches (e.g., plus or minus a few days) or super flexible searches (e.g., a time span in one or more months), using listing arrays that can be rapidly accessed to efficiently identify and return results. The search system can further perform flexible destination searches for different categories of accommodations for display in a viewport (e.g., map bounding box). The system can further perform fuzzy searches to identify and return broader results for flexible queries.
A flexible listings search system can receive and return results for flexible listing searches. For example, the system can perform micro-flexible searches (e.g., plus or minus a few days) or super flexible searches (e.g., a time span in one or more months), using listing arrays that can be rapidly accessed to efficiently identify and return results. The search system can perform flexible destination searches for different categories of accommodations for display in a viewport.
Systems and methods herein describe a listing auto-generation system for generating a listing title and listing description for a listing in an online marketplace. The listing auto-generation system analyzes a set of listing data associated with the listing and generates the listing title and listing description using a machine learning model. The generated listing title and listing description are validated against a set of validation rules and presented on a user interface.
Systems and methods are provided for generating a base visual score for each candidate image of a plurality of images received by a computing system, based on the scene type of each image. For each candidate image, the computing system multiplies the base visual score by a feature importance weight to generate a first visual score, adds respective scene type bonus points to the first visual score to generate a second visual score, and adds diversity scoring points to the second visual score to generate a final visual score for each candidate image. The computing system ranks the candidate images based on the final visual scores and provides a specified number of the top-ranked candidate images to be displayed on a display of the computing device.
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 18/214 - Generating training patterns; Bootstrap methods, e.g. bagging or boosting
G06V 20/30 - Scenes; Scene-specific elements in albums, collections or shared content, e.g. social network photos or video
A flexible listings search system can receive and return results for flexible listing searches. For example, the system can perform micro-flexible searches (e.g., plus or minus a few days) or super flexible searches (e.g., a time span in one or more months), using listing arrays that can be rapidly accessed to efficiently identify and return results. The search system can perform flexible destination searches for different categories of accommodations for display in a viewport.
Systems and methods are provided for receiving a plurality of images corresponding to a listing in an online marketplace, generating a scene type for each image of the plurality of images, and grouping each image into a scene type group of a set of predefined scene types. Each group of images are input into a respective machine learning model specific to the scene type of the group of images to generate a visual score for each image in each group of images, and an attractiveness score is generated for the listing in the online marketplace based on the visual scores for each image in each group of images.
A text-based real-time communication interface, such as a chatbot, is presented to a user for the exchange of customer support information. A user's freeform text input is analyzed using machine learning algorithms to derive the meaning of the input text as well as to determine the user sentiment expressed therein. These determinations may be further supported by signals extracted from session-based activity, which signals can be used to infer the intended workflow of the user and whether or not that workflow was achieved. The expressed user sentiment is considered along with other historical or session-based user data to generate tailored questions and responses to be delivered in real-time to the user. The responses are displayed to the user along with information that routes the user to a workflow resolution.
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
Network site users can be selected to receive a communication based on a network site event, such as incomplete registration. A hybrid user interaction machine learning scheme can select a portion of the selected users based on user interaction estimates and network sampling data. The electronic document sent to the users can have portions that undergo two-pass ranking for ordering of content items to be included in the electronic document, such as an email.
A cost-focused determination of whether to deliver an electronic advertisement or notice to a particular user can be made through a cumulative consideration of the predicted return on investment over each of a plurality of electronic channels. A plurality of channel-specific budget values are calculated for the user, one for each channel, each setting an upper spending limit for advertisement to the user over that channel based on the user's information and their activity on the channel. A global budget is calculated for the user using a weighted aggregation of the channel-specific values, information about the user and their activity with the advertiser, and consideration of “overlap” effects of advertising to the same user on several channels. When managing whether to deliver an advertisement over a channel, if the channel-specific value is lower than the global budget, the advertisement is delivered, and the global budget is decreased by a complementary amount.
One of more unique products can be selected for advertisement over a digital marketing channel. The selection is based on the calculation of a base impression budget, calculated per product per day, which calculation considers information related to a product, including supply and demand at the market level, characteristics of the property, and popularity of the listing. A real-time, or current, impression budget is calculated to determine whether a particular product should be recommended to a user. Every time the product is advertised to a user, a user intent value is calculated, indicating the user's likelihood of purchasing the product within a given period of time, along with the user intent of every user to which the product has been advertised. The user intent calculation may consider information specific to the user, such as the user's activity history and profile. These user intent values are subtracted from the base impression budget to obtain a real-time impression budget. If the real-time budget is greater than zero, the product will be advertised to a user. By these means, a bound is set on the number of times a product may be advertised before it is assumed to be sold.
Systems and methods are provided for receiving a plurality of images corresponding to a listing in an online marketplace, generating a scene type for each image of the plurality of images, and grouping each image into a scene type group of a set of predefined scene types. Each group of images are input into a respective machine learning model specific to the scene type of the group of images to generate a visual score for each image in each group of images, and an attractiveness score is generated for the listing in the online marketplace based on the visual scores for each image in each group of images.
36 - Financial, insurance and real estate services
Goods & Services
Business services, namely, providing information to renters
and property owners in relation to short-term rental
properties and short-term stays; business services, namely,
providing information about programs that provide
compensation to renters and property owners who have
incurred financial costs relating to renting residential or
vacation property; business administration of a
reimbursement program for providing a guarantee for the
reimbursement of costs incurred by property owners when
renting their properties, in exchange for meeting program
requirements. Providing information regarding available insurance products
that cover property owners from financial losses connected
to rental properties; providing information regarding
travelers insurance; providing information regarding renters
insurance; customer services, namely, responding to
customers inquiries for others in the field of insurance;
insurance information services; compiling and organizing
data in the field of insurance for others.
(1) Advertising and promotional services; online advertising and promotional services; advertising and promotional services in the fields of consumer goods and services, travel and lodging.
A cost-focused determination of whether to deliver an electronic advertisement or notice to a particular user can be made through a cumulative consideration of the predicted return on investment over each of a plurality of electronic channels. A plurality of channel-specific budget values are calculated for the user, one for each channel, each setting an upper spending limit for advertisement to the user over that channel based on the user's information and their activity on the channel. A global budget is calculated for the user using a weighted aggregation of the channel-specific values, information about the user and their activity with the advertiser, and consideration of “overlap” effects of advertising to the same user on several channels. When managing whether to deliver an advertisement over a channel, if the channel-specific value is lower than the global budget, the advertisement is delivered, and the global budget is decreased by a complementary amount.
36 - Financial, insurance and real estate services
39 - Transport, packaging, storage and travel services
43 - Food and drink services, temporary accommodation
Goods & Services
Promoting the benefits for others, namely potential hosts, of hosting of temporary stays, hospitality, travel, and the rental and leasing of real estate Providing information in the field of rental and leasing of real estate Provision of travel information Providing information in the field of temporary lodging and accommodations, and information in the field of hospitality services in the nature of provision of temporary accommodation
56.
INCORPORATING INDIVIDUAL AUDIENCE MEMBER PARTICIPATION AND FEEDBACK IN LARGE-SCALE ELECTRONIC PRESENTATION
A presentation service generates an audience interface for an electronic presentation. The audience interface may simulate an in-person presentation, including features such as a central presenter and seat locations for audience members. The audience members may select emotes which may be displayed in the audience interface. The emotes may indicate the audience members' opinion of the content being presented. The presentation service may enable chats between multiple audience members, grouping of audience members private rooms, and other virtual simulations of functions corresponding to in-person presentations.
A presentation service generates an audience interface for an electronic presentation. The audience interface may simulate an in-person presentation, including features such as a central presenter and seat locations for audience members. The audience members may select emotes which may be displayed in the audience interface. The emotes may indicate the audience members' opinion of the content being presented. The presentation service may enable chats between multiple audience members, grouping of audience members private rooms, and other virtual simulations of functions corresponding to in-person presentations.
A presentation service generates an audience interface for an electronic presentation. The audience interface may simulate an in-person presentation, including features such as a central presenter and seat locations for audience members. The audience members may select emotes which may be displayed in the audience interface. The emotes may indicate the audience members' opinion of the content being presented. The presentation service may enable chats between multiple audience members, grouping of audience members private rooms, and other virtual simulations of functions corresponding to in-person presentations.
A presentation service generates an audience interface for an electronic presentation. The audience interface may simulate an in-person presentation, including features such as a central presenter and seat locations for audience members. The audience members may select emotes which may be displayed in the audience interface. The emotes may indicate the audience members' opinion of the content being presented. The presentation service may enable chats between multiple audience members, grouping of audience members private rooms, and other virtual simulations of functions corresponding to in-person presentations.
36 - Financial, insurance and real estate services
Goods & Services
(1) Business services, namely, providing information to renters and property owners in relation to short-term rental properties and short-term stays; business services, namely, providing information about programs that provide compensation to renters and property owners who have incurred financial costs relating to renting residential or vacation property; business administration of a reimbursement program for providing a guarantee for the reimbursement of costs incurred by property owners when renting their properties, in exchange for meeting program requirements.
(2) Providing information regarding available insurance products that cover property owners from financial losses connected to rental properties; providing information regarding travelers insurance; providing information regarding renters insurance; customer services, namely, responding to customers inquiries for others in the field of insurance; insurance information services; compiling and organizing data in the field of insurance for others.
Systems and methods are provided for generating a base visual score for each candidate image of a plurality of images received by a computing system, based on the scene type of each image. For each candidate image, the computing system multiplies the base visual score by a feature importance weight to generate a first visual score, adds respective scene type bonus points to the first visual score to generate a second visual score, and adds diversity scoring points to the second visual score to generate a final visual score for each candidate image. The computing system ranks the candidate images based on the final visual scores and provides a specified number of the top-ranked candidate images to be displayed on a display of the computing device.
Advertising and promotional services; online advertising and promotional services; advertising and promotional services in the fields of consumer goods and services, travel and lodging
Advertising and promotional services; online advertising and promotional services; advertising and promotional services in the fields of consumer goods and services, travel and lodging
Systems and methods are provided for receiving from a first computing device associated with a first user, a request to register a group trip comprising at least one trip item, the request including parameters for the group trip, and receiving authorization from a second computing device associated with a second user to be included in the group trip. The systems and method further providing for receiving from the first computing device, a request to book a trip item for the group trip, approving the request to book the trip item for the group trip based on determining that the trip item meets the parameters for the group trip, and automatically charging a payment device associated with the first user and a payment device associated with the second user according to the parameters related to the group trip.
Systems and methods are provided for search result optimization using machine learning models. A search system uses machine learning models generate a target vector based on query features of a search query and a set of listing vectors based on listing features of listings identified as part of the search query. The target vector represents an estimated optimal listing for the search query and each listing vector represents a corresponding listing identified as part of the search query. The search system determines distances (e.g., Euclidian distance) between each listing vector and the target vector. The determined distances indicate how similar each listing is to the estimated optimal listing for the search query. The search system ranks the listings based on the distances such that listings that are similar to the estimated optimal listing are ranked higher than listing that are not similar to the estimated optimal listing.
36 - Financial, insurance and real estate services
43 - Food and drink services, temporary accommodation
Goods & Services
Providing consumer information about programs that provide compensation to renters and property owners who have incurred financial costs relating to renting residential or vacation property; business administration of a reimbursement program for providing a guarantee for the reimbursement of costs incurred by property owners when renting their properties, in exchange for meeting program requirements; customer services, namely, responding to customers inquiries for others in the field of insurance; compiling business data for insurance purposes Providing information regarding available insurance products that cover property owners from financial losses connected to rental properties; providing information regarding travelers insurance; providing information regarding renters insurance; insurance information services Providing information in the field of short-term temporary lodging and accommodations to renters and property owners
67.
Discovering signature of electronic social networks
A method for predicting the behavior of an electronic social network (ESN) includes identifying one user's connections with other users and creating a data structure in a memory that represents the users and their connections in the ESN. A plurality of data sources for electronic communications between users are analyzed and assigned a relative importance value. A weight is also assigned to each of the connections between the users. The weight is an encoded value computed based on a link structure of the connections where the link structure includes metadata indicating a category and a status of the respective connection. The probability that one user will communicate with one of the other users is calculated based on the analyzed plurality of data sources calculating, and the user's connections with respect to other users are ranked based on the calculated probabilities.
G06F 16/2457 - Query processing with adaptation to user needs
H04L 51/52 - User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail for supporting social networking services
Message display control means updates and displays messages sequentially on a message list screen each time message receiving means receives a message. When input detection means detects a response message, identification means identifies the latest message at the time of detection and the response message. Response message sending means sends the response message as a response to the identified message to other participants upon completion of input of the response message. Therefore, even in the case where the message list screen is updated due to receiving the subsequent message during the input of the response message, the completed response message is able to be sent back to the response object message.
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
The present disclosure relates to the implementation of a pricing structure for the private booking of travel experiences. An experience is offered publicly, so as to be bookable by a plurality of customers, each customer booking a subset of a number of available slots for attendees. A customer may convert the experience from a public experience to a private experience by paying at least a minimum price for the private booking. Where the per person cost would exceed the minimum price, the customer pays an additional per guest value. A plurality of differing pricing rules may be applied in correspondence based on the respective numbers of different types of guests attending the event, or differing date/time instances of the experience.
A system and a method are disclosed for replacing a listing of a canceled booking for a guest user. In an embodiment, an accommodation management system receives an indication that a booking by the guest user has been canceled. The system retrieves, from an attribute database, attributes of the canceled listing and maps each attribute to a set of similar attributes in an equivalence table. The system retrieves, from a listing database, a set of comparable listings, each of which includes one or more of the mapped similar attributes and available during the same time period as the canceled booking. The system books one of the comparable listings for the guest user during the time period by populating a booking data structure with a connection between the comparable listing and the guest user.
A computer-implemented method of posting content to a social medium comprises receiving content posted by a user along with an associated posting time which indicates when the user selected an option to post the content to the social medium; determining that publication of the content posted by the user is dependent on a trigger; and in response to determining that publication of the content is dependent on the trigger, storing the content with the associated posting time and suspending publication of the content until the trigger is satisfied such that the posting time published with the content indicates a time prior to transmission of the content from an electronic device to a server for publishing.
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
H04L 51/52 - User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail for supporting social networking services
H04L 51/222 - Monitoring or handling of messages using geographical location information, e.g. messages transmitted or received in proximity of a certain spot or area
H04L 67/10 - Protocols in which an application is distributed across nodes in the network
A method for depicting location attributes in a map environment. The method includes receiving a request for parameters about a first type of location. The method includes determining a first set of directional arrows, where each directional arrow is associated with a location and has a first set of properties based on the parameters about the first type of location. The method further includes determining a selection of a first directional arrow, which is associated with a first location, from the first set of directional arrows. Modifications to the first set of directional arrows are made based on the selection of the first directional arrow.
A system and a method are disclosed for managing a travel itinerary by calculating pre-event triggers and interfacing with travel service providers to streamline travel services for a traveler. In an embodiment, a travel management system receives an electronic itinerary for a traveler, the electronic itinerary comprising a plurality of events. Based on the electronic itinerary, the travel management system identifies an event of the plurality of events and event managers for the events. The travel management system determines pre-event triggers for the events. The travel management system calculates trigger times for the pre-event triggers. The travel management system transmits, at the trigger times, the pre-event triggers to the event managers for execution of a function corresponding to the event.
A system and a method are disclosed for replacing an accommodation of a canceled booking for a guest user. In an embodiment, an accommodation management system receives, from a homestay application, an indication that a booking for the accommodation in a region by the guest user over a time period has been canceled. The system retrieves a homestay listing associated with the booking and retrieves attributes of the homestay listing. The system maps each attribute to a set of similar attributes in an equivalence table. The system retrieves a set of available hotel listings in the region for the same time period and determines attributes of each available hotel listing. The system determines a set of comparable hotel listings that each include similar attributes to the homestay listing and sends a command to book a comparable hotel listing the guest user during the time period.
G06F 16/908 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
A system and a method are disclosed for augmenting a required curriculum of an individual in a nomadic group. The system retrieves, from a client device, a request for an accommodation recommendation from the nomadic group, which includes an individual with a required curriculum. The system maps the curriculum to destinations in a destination database and determines a set of geographic regions including the destinations. The system optimizes an accommodation recommendation based on available listings in the geographic regions and geographic locations of the destinations and transmits, for display on a user interface at the client device, a user interface comprising the accommodation recommendation.
A system and a method are disclosed for satisfying a curriculum during nomadic travel. In an embodiment, an accommodation management system receives, from a client device, information describing a desired curriculum scope and a time period. The system optimizes a curriculum based on subjects mapped from the curriculum scope and the time period. The system maps the curriculum to destinations and determines a set of geographic regions including the destinations. The system determines a set of geographic regions including the destinations. For each geographic region, the system retrieves, from a listing database, listing available in the geographic region during a subset of the time period. The system ranks the retrieved listings for each geographic region based on the destinations and transmits, for display on a user interface at the client device, an accommodation recommendation including listings in one or more of the geographic regions.
G06Q 30/02 - Marketing; Price estimation or determination; Fundraising
G06Q 30/06 - Buying, selling or leasing transactions
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
A system and a method are disclosed for providing specific items in an accommodation for a user. The system may parse an accommodation review for an accommodation left by a subscription living user. The system may determine an item type that the subscription living user mentioned in the accommodation review. The system may identify a specific item for the item type mentioned by the subscription living user. The system may determine that the subscription living user will be staying in a subsequent accommodation. the system may provide, for display to the subscription living user, a rendering of the specific item superimposed on an image of the subsequent accommodation. The system may transmit, automatically in response to the user booking the subsequent accommodation, a request to a vendor to provide the specific item for the subsequent accommodation.
A system and a method are disclosed for optimally ranking and indexing accommodation listing information based on a set of constraints corresponding to a travel activity goal input on a client device. In an embodiment, an accommodation management system receives a travel activity goal input by a guest user on a client device with a corresponding set of constraints. Based on the constraints, the accommodation management system determines a set of geographic coordinates corresponding to the travel activity, and further identifies the set of candidate accommodation listings with accommodations within a threshold distance from the geographic coordinates. The accommodation management system filters and ranks the candidate accommodation listings based on the constraints, and sends a recommendation to the guest user for display on the client device which includes one or more of the ranked accommodation listings.
An approach is described for addressing propagation of inaccurate information in a social networking environment. An associated method may include identifying inaccurate information within the social networking environment, facilitating creation of countering content to address the inaccurate information, and disseminating the countering content. The countering content may be determined by identifying behavior of one or more users among a plurality of users within the social networking environment. Identifying the inaccurate information within the social networking environment may include receiving information provided within the social networking environment. Upon determining that the received information is factual and thus objectively verifiable, it may be determined whether the received information matches analogous information verified as accurate. Upon determining that the received information does not match the analogous information verified as accurate, the received information may be marked as inaccurate.
G06F 16/9535 - Search customisation based on user profiles and personalisation
G06F 40/289 - Phrasal analysis, e.g. finite state techniques or chunking
H04L 51/52 - User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail for supporting social networking services
H04L 51/216 - Handling conversation history, e.g. grouping of messages in sessions or threads
In a roofing structure, two roof panels with different slopes and lengths are positioned back-to-back, the vertical back walls of the panels having a uniform height. The seam between the two differently-sloped panels are connected by a ridge cap set at a uniform height. The ridge cap covers the seam, extending on both sides to a distance from the back walls of the roof panels sufficient to create a capillary break therefrom (preventing moisture migration) and then downwards and slightly towards the back walls of the roof panels, thereby using gravity to direct the water into the downward sloping roof panels.
E04C 3/00 - Structural elongated elements designed for load-supporting
E04D 3/366 - Connecting; Fastening by closing the space between the slabs or sheets by gutters, bulges, or bridging elements, e.g. strips
E04D 3/24 - Roof covering by making use of flat or curved slabs or stiff sheets with special cross-section, e.g. with corrugations on both sides, with ribs, flanges, or the like
E04B 7/20 - Roofs consisting of self-supporting slabs, e.g. able to be loaded
A system and a method are disclosed for obscuring a location of an accommodation. A booking accommodation application obscures an exact location of the accommodation provided by a host. The booking accommodation application displays a visual representation of the accommodation on a map interface. Even when the map interface is zoomed in, the visual representation maintains the obfuscation of the accommodation.
A position debiased search system can avoid bias towards top-ranked search results using a position-trained machine-trained model. Past positions for listings can be input into the model with added noise and low-ranked results to train the model to generate rankings that do not exhibit position bias. A network site can implement the position debiased search system to generate network site results that can generate accurate user results in real time as users browse the network site.
Network site users can be selected to receive a communication based on a network site event, such as incomplete registration. A hybrid user interaction machine learning scheme can select a portion of the selected users based on user interaction estimates and network sampling data. The electronic document sent to the users can have portions that undergo two-pass ranking for ordering of content items to be included in the electronic document, such as an email.
G06F 16/90 - Information retrieval; Database structures therefor; File system structures therefor - Details of database functions independent of the retrieved data types
G06F 16/9535 - Search customisation based on user profiles and personalisation
H04L 51/00 - User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail
Systems and methods are provided for search result optimization using machine learning models. A search system uses machine learning models generate a target vector based on query features of a search query and a set of listing vectors based on listing features of listings identified as part of the search query. The target vector represents an estimated optimal listing for the search query and each listing vector represents a corresponding listing identified as part of the search query. The search system determines distances (e.g., Euclidian distance) between each listing vector and the target vector. The determined distances indicate how similar each listing is to the estimated optimal listing for the search query. The search system ranks the listings based on the distances such that listings that are similar to the estimated optimal listing are ranked higher than listing that are not similar to the estimated optimal listing.
09 - Scientific and electric apparatus and instruments
42 - Scientific, technological and industrial services, research and design
Goods & Services
Downloadable computer software and application software for
mobile devices, namely, software that allows users to find,
research, analyze, track, manage, compare, personalize,
customize, book, rate and share with others special offers
and promotions and opinions in the fields of consumer goods
and services, namely, travel and lodging. Software as a Service (SaaS) and Platform as a Service
(PaaS) services that allow users of web-based online
software, handheld devices and mobile devices to find,
research, analyze, track, manage, compare, personalize,
customize, book, rate and share with others special offers
and promotions and opinions in the fields of consumer goods
and services, namely, travel and lodging.
Systems and methods are provided for receiving image data via a camera of a computing device, the image data comprising a plurality of image frames; displaying a 3D reconstruction of the image data on a graphical user interface (GUI) displayed on a computing device as the image data is received and the 3D reconstruction of the image data is generated; detecting at least one object corresponding to one or more of a plurality of predefined object types in the image data; determining dimensions of the at least one object in 3D space based on the 3D reconstruction of the image data; and displaying in the GUI the at least one detected object.
Systems and methods are provided for receiving image data via a camera of a computing device, the image data comprising a plurality of image frames; displaying a 3D reconstruction of the image data on a graphical user interface (GUI) displayed on a computing device as the image data is received and the 3D reconstruction of the image data is generated; detecting at least one object corresponding to one or more of a plurality of predefined object types in the image data; determining dimensions of the at least one object in 3D space based on the 3D reconstruction of the image data; and displaying in the GUI the at least one detected object.
Systems and methods are provided for accessing a three-dimensional (3D) image comprising a 3D mesh comprising a plurality of vertices and each vertex of the plurality of vertices having respective 3D coordinates within a space of the 3D mesh. The systems and methods further provide for generating a subset of the plurality of vertices comprising vertices that are within a specified height range and have a specified orientation. The systems and methods further provide for generating a two-dimensional (2D) grid corresponding to the 3D mesh, applying the subset of the plurality of vertices to the 2D grid, and rendering a 2D image of the space comprising an outer border corresponding to the size and shape of the 2D grid and indications of walls within the space based on the applied subset of the plurality of vertices.
A reusable modular housing system has a gridded structure comprising reusable components with dimensions corresponding to a two-unit system. The structure has floor and ceiling grids with dimensions that correspond to multiples of a first unit of measurement. The vertical beams that connect the floor and ceiling grids are spaced apart at dimensions that also correspond to multiples of the first unit of measurement. The structure has a variety of other components that can be coupled to the floor and ceiling grids and the vertical beams, and those other components have dimensions that correspond to a multiple of a second unit of measurement. Dimensions of the structure can vary, but each of the component parts can be detachably coupled into the gridded structure, so as to fit within the grid's dimensions based on respective multiples of the first unit of measurement and the second unit of measurement. The structure can be assembled into a first configuration, and when use of the structure is completed, the structure can be disassembled into its component parts which can be later assembled into the first configuration or a different second configuration. Use of a two-unit system of dimensions for the system allows for component parts to be reused on the same or other structures designed within the same dimensional system.
E04B 1/343 - Structures characterised by movable, separable, or collapsible parts, e.g. for transport
E04B 1/348 - Structures composed of units comprising at least considerable parts of two sides of a room, e.g. box-like or cell-like units closed or in skeleton form
E04B 1/24 - Structures comprising elongated load-supporting parts, e.g. columns, girders, skeletons the supporting parts consisting of metal
92.
Log-aided automatic query expansion approach based on topic modeling
A base query having a plurality of base query terms is obtained. A plurality of problem log files are accessed. Words, contained in a corpus vocabulary, are extracted from the plurality of problem log files. Based on the words extracted from the plurality of problem log files, a first expanded query is generated from the base query. The corpus is queried, via a query engine and a corpus index, with a second expanded query related to the first expanded query.
Systems and methods are disclosed for retrieving, from a database, over a network, historical routing data for multiple attributes and determining, for each attribute, based on its respective historical routing data, whether processing volume and processing error rates for each attribute exceed respective threshold. If both processing volume and error rate exceed their respective thresholds, the systems and methods describe herein calculate, for each qualifying attribute, a degree to which routing for each attribute can be improved. The systems and methods described herein output a ranking for each qualifying attribute based on their respective degrees to which routing can be improved for the respective attributes.
Systems and methods are provided for extracting a plurality of features for a listing from a datastore comprising a plurality of listings and a plurality of features for each of the plurality of listings, determining a cluster of similar listings to the listing and generating a set of cluster features for the cluster of similar listings, analyzing the set of cluster features for the cluster of similar listings based on a booking price, using a first trained machine learning model to determine a cluster-level probability of booking the listing on the given date, analyzing the plurality of features for the listing using the booking price, using a second trained machine learning model to determine a listing-level probability of booking the listing on the given date, and generating a final probability of booking by combining the cluster-level probability of booking and the listing-level probability of booking.
Systems and methods are disclosed for retrieving, from a database, over a network, historical routing data for multiple attributes and determining, for each attribute, based on its respective historical routing data, whether processing volume and processing error rates for each attribute exceed respective threshold. If both processing volume and error rate exceed their respective thresholds, the systems and methods describe herein calculate, for each qualifying attribute, a degree to which routing for each attribute can be improved. The systems and methods described herein output a ranking for each qualifying attribute based on their respective degrees to which routing can be improved for the respective attributes.
Systems and methods are provided for extracting a plurality of features for a listing from a datastore comprising a plurality of listings and a plurality of features for each of the plurality of listings, determining a cluster of similar listings to the listing and generating a set of cluster features for the cluster of similar listings, analyzing the set of cluster features for the cluster of similar listings based on a booking price, using a first trained machine learning model to determine a cluster-level probability of booking the listing on the given date, analyzing the plurality of features for the listing using the booking price, using a second trained machine learning model to determine a listing-level probability of booking the listing on the given date, and generating a final probability of booking by combining the cluster-level probability of booking and the listing-level probability of booking.
Text including at least a first term can be presented on a display. An enterprise glossary can be queried to identify at least a first curation parameter assigned to the first term. A first score can be determined for the first term based, at least in part, on the first curation parameter assigned to the first term. The first score can be assigned to a first data value. The first data value can be presented on the display.
Disclosed are ways to generate and present recommendations which provide a user with the ability to explore the follow-on consequences of accepting the recommendations. In some aspects, a method includes receiving a first user input including a recommendation topic, presenting, via a display, an exploration structure including a node corresponding to the recommendation topic, receiving data corresponding to the node from a knowledge repository, analyzing the received data to determine at least one follow-on recommendation based on the node, and presenting each determined follow-on recommendation in the exploration structure as a child node of the node corresponding to the recommendation topic.
A behavior detection module receives a training database and applies a transformation to the attributes that improves the uniformity of the values associated with each attribute. The transformed training database is used to construct a random forest classifier (RFC). The RFC includes a plurality of decision trees and generates a classification label estimate for a data entry with a plurality of attributes. The classification label estimate is determined based on classification estimates from the plurality of decision trees. Each parent node of a decision tree is associated with a condition of a transformed attribute that directs the data entry to a corresponding child node depending on whether the condition is satisfied or not. The data entry is directed through the tree to one out of a set of leaf nodes, and a classification label associated with the leaf node.
09 - Scientific and electric apparatus and instruments
42 - Scientific, technological and industrial services, research and design
Goods & Services
Downloadable computer software and application software for
mobile devices, namely, software that allows users to find,
research, analyze, track, manage, compare, personalize,
customize, book, rate and share with others special offers
and promotions and opinions in the fields of consumer goods
and services, namely, travel and lodging. Software as a service (SaaS) and Platform as a service
(PaaS) services that allow users of web-based online
software, handheld devices and mobile devices to find,
research, analyze, track, manage, compare, personalize,
customize, book, rate and share with others special offers
and promotions and opinions in the fields of consumer goods
and services, namely, travel and lodging.
