Opentable, Inc.

Yige Wang

Jeremy Ryan Schiff

Corey Layne Reese

Brett Matthew Westervelt

Steven Charles Schlansker

Paul Kenneth Twohey

Scott Goodson

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.

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East Palo Alto, CA, United States of America

Yige Wang