Opentable, Inc.

Jeremy Ryan Schiff

Corey Layne Reese

Steven Charles Schlansker

Paul Kenneth Twohey

Sourav Chatterji

Leejay Wu

Yige Wang

Brett Matthew Westervelt

Scott Goodson

Scott Paul Goodson

Christopher Eric Berner

Embodiments of the invention relate to a computer-implemented method and system for generating personalized recommendations for a target user based at least on stored data about the target user. The method comprises obtaining, at the server computer, data from a plurality of data sources, including entity data associated with a plurality of entities, stored in an entity database, or personal data associated with a plurality of users, stored in a user database. The personalized recommendations system then merges the entity data or personal data and maps the entity or personal data to a corresponding entity or target user, respectively. The entity or personal data is differentiated, a relevance is determined, a weight is assigned to the data and corresponding source to canonicalize the data, the respective databases are updated with the corresponding data, and then a set of personalized recommendations to the target user is generated using the updated databases.

Computer system and method for analyzing data sets and generating personalized recommendations

Embodiments of the invention relate to methods and systems for evaluating entities for a target user, the method comprising obtaining, at a server computer, entity data from a plurality of data sources. The entity data is then stored in an entity database. The method further comprises merging the entity data from the plurality of data sources, mapping the entity data to a corresponding entity, and differentiating the entity. Then a relevance is determined associated with the entity data and data source. The method further comprises generating a set of entity evaluations to the target user using the relevance, determining a set of one or more entities relevant to the primary user based on the entity data, user data, and the relevance, with an initial order of relevance, and displaying, on a user device, the set of relevant entities to the target user in the order of relevance.

Method and apparatus for quickly evaluating entities

Techniques for context-based queryless presentation of items are described. Without receiving an explicit query, an inferred query is determined based on a first set of context signals associated with a triggering event. Items matching the inferred query are selected based on a second set of one or more context signals associated with the triggering event. One or more results items identifying the one or more matching items are caused to display. Result items may be displayed in association with an explanation that identifies context values used to select an item or one or more attributes of the item that are relevant to a user or the inferred query.

Context-based queryless presentation of recommendations

Techniques for context-based queryless presentation of recommendations are described. Without receiving an explicit query, an inferred query is determined based on a first set of context signals associated with a recommendation triggering event. Items matching the inferred query are selected based on a second set of one or more context signals associated with the recommendation triggering event. One or more results items identifying the one or more matching items are caused to display. A result items may be displayed in association with an explanation that identifies context values used to select an item for recommendation or one or more attributes of the item that are relevant to a user or the inferred query.

Embodiments of the invention relate to a computer-implemented method and system for providing personalized recommendations for a target user based at least on stored data about the target user. The method comprises obtaining a plurality of feedback data from a plurality of users, wherein the feedback data comprises an indication of a media object, a response obtained from target user related to the feedback data, and at least one demographic data element associated with the target user. A set of personalized recommendations for the target user are identified based at least on stored data about the target user and the feedback data related to the user. The personalized recommendations system identifies media objects to potentially provide to the target user, and selects or filters the identified media objects to form a set of personalized media objects associated with the set of personalized recommendations.

Computer system and method for analyzing data sets and providing personalized recommendations

Embodiments of the invention relate to a category based navigation system obtaining user data related to a plurality of users relevant to the primary user. The method further comprises obtaining entity data associated with an entity in a plurality of entities. The category based navigation system then determines one or more entities relevant to the primary user, and determines an initial order of relevance of a set of relevant entities. The method further comprises categorizing and displaying the set of relevant entities with an initial categorization on a user device to the primary user. The category based navigation system may then obtain, via the user device, user feedback, adjust the initial categorization and initial order of relevance based on the user feedback; and display the adjusted categorization and adjusted order of relevance of the set of relevant entities to the primary user on the user device.

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Portola Valley, CA, United States of America

Jeremy Ryan Schiff