Linkedin Corporation

Microsoft Technology Licensing, LLC

Roshan Rajesh Sumbaly

Samir Mavji Shah

Mitul Tiwari

Curtis Wang

Ankit Gupta

Parinkumar D Shah

Raghu Ram Hiremagalur Venkatesh

Shubham Gupta

Swapnil Ghike

A system may receive, at least in part from an update database, a plurality of updates to a plurality of profiles that individually describe ones of a plurality of users of a social network. The system may process, using a batch processor, at least some of the plurality of updates to generate a consolidated update indicative of a status of at least some of the plurality of profiles. The system may transmit the consolidated update to the update database. The system may display the consolidated update on an update stream of the social network corresponding to at least one of the plurality of users.

Batch-computed  activity stream updates

The disclosed embodiments provide a system for processing data. During operation, the system stores a set of feed updates associated with a set of entities in descending chronological order within a set of resizable blocks. For each entity in the set of entities, the system generates an index containing one or more lists of resizable blocks storing a subset of the feed updates associated with the entity, wherein the one or more lists are sorted in descending chronological order. The system then uses the index to generate a content feed containing a selection of the feed updates for outputting to a viewer.

Efficient indexing of feed updates for content feeds

Disclosed in some examples are methods, systems, and machine-readable mediums which provide a relevance engine for determining a relevance of an individual (either a non-member or another member) to another individual (either a non-member or another member). This relevance engine may use signals in the form of data that the social networking service may learn about the individuals to determine how relevant the individuals are to each other.

Techniques to facilitate recommendations for non-member connections

Disclosed in some examples are methods, systems, and machine-readable mediums which provide a relevance engine for determining a relevance of an individual (either a non-member or another member) to another individual (either a non-member or another member). This relevance engine may use signals in the form of data that the social networking service may learn about the individuals to determine how relevant the individuals are to each other. Example applications may include ordering of connection invitations in a social networking service.

Growing community of inventors

Santa Clara, CA, United States of America

Roshan Rajesh Sumbaly