Google Inc.

Justin Lewis Kosslyn

Andrew Stephen Tomkins

Andre Rohe

Todd Christopher Jackson

Sangsoo Sung

Dandapani Sivakumar

Andrew Ames Bunner

Luca De Alfaro

Ya Luo

Ray Su

Sasha Sobol

Cameron Knox Adams

Mayur Dhondu Datar

Jonathan Terleski

Daniel Wesley Dulitz

Alexander Sobol

Robert Spiro

Shaun Z Modi

Jessica Ko

Christopher Wiggins

Chris Wiggins

Sucharitha Vasudevan

A system and method for generating a stream of content includes a content stream module that generates a model based on user input and/or prior activities using heterogeneous data sources. The heterogeneous data sources include search, entertainment, social activity and activity on third-party sites. The content stream module retrieves candidate content items that have interests that are similar to the user. The candidate content items are compared to the model and scored based upon interestingness of the content item to the user. The content stream module generates the stream of content from the candidate content items.

Scoring stream items with models based on user interests

A system and method for generating a stream of content with candidate content items associated with a likelihood of being interesting to a user. A model generation engine generates a model for a user. A scoring engine obtains candidate content items and compares candidate content items to a model to determine the most interesting content items. A user interface engine organizing first and second content items in a first direction and a third content item in a second direction. The user interface engine receives feedback that includes a request for additional content items or a request to remove an interest associated with a selected content item from the model. The model generation engine updates the model in response to feedback.

Organizing a stream of content

A system and method for generating a real-time stream of content from heterogeneous data sources and a real-time index. The heterogeneous data sources include search, entertainment, social activity and activity on third-party sites. A fetching unit retrieves recent content that is indexed in the real-time index according to keywords. A model generation engine generates a model based on user activities. The mixer compares candidate content items from the heterogeneous data sources and the real-time index to the model to generate scores for each item and generates a stream of content based on the scores.

Scoring stream items in real time

A system and method for generating a channel includes a channel engine that retrieves candidate content items based on a topic from heterogeneous data sources. The channel engine generates a stream of content with selected content items and populates the stream of content for the channel and providing the stream of content to users associated with the channel. In response to receiving feedback, the channel engine modifies the at least one topic based at least in part on the feedback. The scoring engine generates a second stream of content from the first stream of content that is personalized for the first user based at least in part on a model. Other users can subscribe to the second stream.

Stream of content for a channel

A system and method for generating a stream of content for a channel. The channel application includes a content categorizer, a scoring engine and a channel engine. The content categorizer categorizes new content items received from heterogeneous data sources. The channel engine identifies a channel category for a user based at least in part on at least one of a historical trend and a user activity. The scoring engine queries the new content items based on the channel category and at least one other channel attribute. The scoring engine retrieves candidate content items that include the channel category and the other channel attribute. The scoring engine then generates a stream of content from the candidate content items for the channel.

Generating a stream of content for a channel

Computer-implemented methods for determining whether to prompt a user to sign in to view content are provided. In one aspect, a method includes receiving a request from a non-authenticated device to view content, and determining whether the device comprises a personalized content module indicating whether the device has previously been authenticated to view the content in a personalized format. The method also includes providing, for display, a notification to the device to provide authentication when the personalized content module indicates that the device has previously been authenticated to view the content in a personalized format. Systems, graphical user interfaces, and machine-readable media are also provided.

Personalized content access prompt

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San Francisco, CA, United States of America

Justin Lewis Kosslyn