Google Inc.

Huazhong Ning

Hrishikesh Balkrishna Aradhye

David A Ross

Lichan Hong

Douglas Eck

Jilin Chen

Zhen Li

Ed Huai-Hsin Chi

Christopher Tim Althoff

Peng Dai

Tianjiao Zhang

Mohamad Tarifi

Rodrigo Lima Carceroni

Wei Hua

Wei Chai

Marius Renn

Haichun Chen

Emre Sargin

Implementations provide an improved system for presenting search results based on entity associations of the search items. An example method includes generating first-level clusters of items responsive to a query, each cluster representing an entity in a knowledge base and including items mapped to the entity, merging the first-level clusters based on entity ontology relationships, applying hierarchical clustering to the merged clusters, producing final clusters, and initiating display of the items according to the final clusters. Another example method includes generating first-level clusters from items responsive to a query, each cluster representing an entity in a knowledge base and including items mapped to the entity, producing final clusters by merging the first-level clusters based on an entity ontology and an embedding space that is generated from an embedding model that uses the mapping, and initiating display of the items responsive to the query according to the final clusters.

Clustering search results

A system and method of recommending a bundle of content items to a user, including storing a plurality of content items in a computer system, determining a respective co-selection score for each pair of content items among the plurality of content items, the co-selection score indicating a probability that a given pair of content items among the plurality of content items will both be downloaded by a user of the computer system, and outputting, to a first user, a plurality of content items comprising a sub-set of the plurality of content items.

System and method to recommend a bundle of items based on item/user tagging and co-install graph

The user feedback module receives from a user device a selection of a seed media item. The seed media item includes a seed label. The user feedback module further generates a list, the list includes the seed label and a set of related labels based on the seed label. The seed label and each related label include a separate label weight. The user feedback module also identifies multiple media items associated with an associate label. The associate label includes at least one of the seed label or a related label of the first set of related labels. The user feedback module also transmits to the user device a first media item from the multiple media items. The user feedback module adjusts the label weight of the associate label based on a user feedback on the first media item.

Adaptive music and video recommendations

A method is described that includes comprising receiving, by a first computing device and from a second computing device, an indication of user interaction with a first application. The method also includes determining, by the first computing device and based on the user interaction with the first application, a user engagement score associated with the first application, the user engagement score indicating at least one of how frequently or how long the user uses the first application. The method also includes responsive to determining that the user engagement score does not satisfy a threshold user engagement score, determining, by the first computing device and from a set of applications that are alternatives to the first application, a second application to substitute for the first application. The method further includes sending, by the first computing device and to the second computing device, for display, an indication of the second application.

Recommending substitute applications

A system and method for associating videos with geographic locations is disclosed. The system comprises a communication module, a location module, a tagging module and a database association module. The communication module receives a video uploaded by a content provider and a set of video data describing the video. The location module determines that the video describes a geographic location included in a geographic map based at least in part on the video data. The tagging module determines one or more travelling tags for the video based at least in part on the video data. The database association module associates the video and the one or more travelling tags with the geographic location so that the video with the one or more travelling tags is included in the geographic map.

Associating video content with geographic maps

A method for creating personalized and continuous playlists for a content sharing platform based on user history is disclosed. The method includes grouping content items into groups based on whether users access the content items close together in time and whether the content items appear together in search results and are both selected by the users, the groupings representing a relatedness between pairs of the content items, determining probabilities that the users transition between the groups when viewing the content items, assigning, for a user of the users, a score to each group in a subset of the groups, wherein the scores represents preferences of the user for viewing the content items of the subset, selecting, for the user, a group in the subset based on the assigned scores and the probabilities, and providing a content item from the selected group to include in a playlist generated for the user.

Creating personalized and continuous playlists for a content sharing platform based on user history

A user feedback module, executable by a processing device from memory is disclosed. The user feedback module receives from a user device a selection of a seed media item. The seed media item includes a seed label. The user feedback module further generates a list, the list includes the seed label and a set of related labels based on the seed label. The seed label and each related label include a separate label weight. The user feedback module also identifies multiple media items associated with an associate label. The associate label includes at least one of the seed label or a related label of the first set of related labels. The user feedback module also transmits to the user device a first media item from the multiple media items. The user feedback module adjusts the label weight of the associate label based on a user feedback on the first media item.

A method includes generating a ranking model and a baseline mixing weight for each latent user category from a plurality of latent user categories based on a community preference dataset and one or more latent variables that relate the users from the community of users to the latent user categories. The method also includes generating a personalized mixing weight for each latent user category for a specified user based on an individual preference dataset, the ranking models for the latent user category, and one or more latent variables that relate the specified user to the latent user categories. The method also includes adjusting the personalized mixing weight for each latent user category for the specified user based on the baseline mixing weights, and generating ranking output for at least some objects from the plurality of objects using the personalized mixing weights and the ranking models.

Latent user models for personalized ranking

A system, apparatus, and method for video categorization using heterogeneous signals are disclosed. One aspect of the disclosed embodiments is a method for categorizing a plurality of video streams. The method includes determining a plurality of features of at least some of the plurality of video streams, determining a category of a first video stream of the plurality of video stream based on its plurality of features, identifying, using a processor, a relationship between the first video stream and a second video stream of the plurality of videos, the relationship having an associated weight, and updating, using the processor, the category of the first video stream based on a first message determined using the associated weight.

Video categorization using heterogeneous signals

Disclosed are methods for automatically generating commands to transform a video sequence based on information regarding speaking participants derived from the audio and video signals. The audio stream is analyzed to detect individual speakers and the video is optionally analyzed to detect lip movement to determine a probability that a detected participant is speaking. Commands are then generated to transform the video stream consistent with the identified speaker.

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San Jose, CA, United States of America

Huazhong Ning