Google Inc.

Jennifer Su

Christian Posse

Mark T Rivera

The present disclosure is directed to generating search results, recommendations, and/or the like. In particular, the methods and systems of the present disclosure can: receive data describing one or more aspects of an entity; determine, based at least in part on the aspect(s) of the entity, one or more additional aspects of the entity; determine, based at least in part on the aspect(s) of the entity and the additional aspect(s) of the entity, a metric indicating a reputational prominence of the entity relative to multiple other entities of similar type; generate, based on the metric, one or more search results, recommendations, and/or the like; and communicate, to a computing device (e.g., for display, and/or the like), data indicating the search result(s), recommendation(s), and/or the like.

Methods and systems for generating search results and recommendations based on multi-sourced two-way correspondence and relative entity prominence

The present disclosure is directed to generating search results, recommendations, and/or the like. In particular, the methods and systems of the present disclosure can: receive data describing one or more aspects of entities of different types; determine, based at least in part on the aspect(s) of the entities, one or more additional aspects of the entities; determine, based at least in part on the additional aspect(s) of the entities, a metric indicating an extent to which the entities correspond to one another; generate, based on the metric, one or more search results, recommendations, and/or the like; and communicate, to a computing device (e.g., for display, and/or the like), data indicating the search result(s), recommendation(s), and/or the like.

Systems and methods for providing relevant explanations for recommended content are provided. In one embodiment, a computer-implemented method includes obtaining data indicative of one or more parameters associated with a user. The method includes determining recommended content for the user based at least in part on the one or more parameters associated with the user. The recommended content is associated with a recommended engagement for the user. The method includes generating an explanation for the recommended content for the user based at least in part on the one or more parameters associated with the user. The explanation is indicative of why the recommended engagement is recommended for the user. The method includes providing data indicative of the recommended content and the explanation for the recommended content for display on a user interface via a display device.

System for determining and displaying relevant explanations for recommended content

Systems and methods for autosuggesting related objects to a user are provided. In one embodiment, a method includes receiving data indicative of a user input. The method includes identifying one or more ontologies based, at least in part, on the user input. Each ontology is associated with a category that is related to the user input. Each ontology includes a plurality of object types, each object type including one or more terms. The method includes determining one or more suggested related objects based, at least in part, on the user input and one or more of the plurality of object types. The one or more suggested related objects include one or more of the terms that are related to the user input. The method includes providing data indicative of the suggested related objects for display on a user interface via a display device.

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San Francisco, CA, United States of America

Jennifer Su