Linkedin Corporation

Microsoft Technology Licensing, LLC

Curtis Wang

Mitul Tiwari

Samir Mavji Shah

Roshan Rajesh Sumbaly

Shaunak Chatterjee

Aastha Jain

Shipeng Yu

Ankit Gupta

Parinkumar D Shah

Changji Shi

Swapnil Ghike

Vivek Nelamangala

Pingjie Xiao

Banu Muthukumar

Eric Brownrout

A notification platform for distribution of notification content in an on-line social network system, on-line and in near real time, is described. As a new notification is detected in the continuous stream of notifications triggered by time-sensitive events, the near real time notifications distribution system determines member profiles representing potential recipients of the notification by traversing a relationship graph. The relationship graph has nodes representing member profiles, as well as other entities maintained in the on-line social network system. The edges of the relationship graph represent relationships between entities represented by the associated nodes. For each member profile representing a potential recipient of the notification, the near real time notifications distribution system generates a relevance score, which is used to determine whether the notification is to be delivered to the potential recipient.

Near real time notifications distribution platform

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.

Connection invitation ordering

A system and method for contextual connection recommendation includes obtaining, with a processor from a database, contextual data and social graph data related to a pair of members of a social network who are not currently connected on the social network. A connection base score between the pair of members is generated based on the social graph data. A recommendation modifier is generated based on the contextual data. A connection recommendation modified score is determined by applying the recommendation modifier to the base score. A connection recommendation is provided to at least one of the pair of members based, at least in part, on the connection recommendation modified score.

Contextual connection recommendation in a social network

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Santa Clara, CA, United States of America

Curtis Wang