Google Inc.

Benjamin Liebald

Palash Nandy

Christina Ilvento

Jamie Davidson

Dasarathi Sampath

Ye Niu

Patrick Hung

Behshad Behzadi

Monika Hildegard Henzinger

Yu-To Chen

Yaniv Bernstein

Richard Tucker

Junning Liu

Stefan Burkhardt

A system and method for developing a user's profile based on the user's interaction with content items. A module on the client rendering the content items or the service including the content items tracks the user's interactions with the content items and transmits the tracked data to a user analysis module. The user analysis module determines the topics associated with the interacted upon content items. The user analysis module then selects the topics for the user's profiles based on the received tracked data and the associated topics. The selected topics are stored in association with the user profile.

Topic based user profiles

A personal content stream comprising a plurality of videos is generated for a user. The user selects topics used in the generation of a personal content stream. The plurality of user selected topics is expanded to include topics related to one or more of the user selected topics. Each of the topics in the expanded plurality of topics includes a topic weight. Videos are selected that are related to one or more of the expanded plurality of topics to generate a plurality of stream videos. Additional videos are selected and added to the plurality of stream videos as the user watches videos. The topic weights are adjusted during video playback based on feedback from the user.

Personal content streams based on user-topic profiles

Updating personal content streams based on feedback

A system and method for developing a user's profile based on the user's interaction with content items. A module on the client rendering the content items or the service including the content items tracks the user's interactions with the content items and transmits the tracked data to a user analysis module. The user analysis module determines the topics associated with the interacted upon content items. The user analysis module then selects the topics for the user's profiles based on the received tracked data and the associated topics. The selected topics are mapped to topic clusters and the topic clusters are stored in association with the user profile. Recommendations for a user are made based on the topic clusters associated with the user'profile.

Recommendations based on topic clusters

The present disclosure includes, among other things, systems, methods and program products for selecting subsequences (shingles or tuples) generated from sequences of tokens.

Algorithms for selecting subsequences

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San Francisco, CA, United States of America

Benjamin Liebald