Linkedin Corporation

Microsoft Technology Licensing, LLC

Yurong Shi

Anmol Bhasin

Junghoon (Andrew) Ahn

Abhishek Gupta

Christian Posse

Jian H Li

Jacob Kessler

Lizabeth Li

Venu Javarappa

Yi Zheng

Yongzheng Zhang

Weidong Zhang

Chi-Yi Kuan

Jonathan David Traupman

Weiqin Ma

Junghoon Andrew Ahn

Bin Wu

SangHyun Park

Hong Lu

Srihari R Duddukuru

Tarun Kumar

Liwen Zhang

Systems and methods for reducing a churn rate associated with subscribers of social network services are described. In some example embodiments, the systems and methods may access activity information associated with a former subscriber of a social network service, compare the accessed activity information to activity information associated with subscribers of the social network service, identify one or more differences between the activity information associated with the former subscriber of the social network service and the activity information associated with the subscribers of the social network service, and perform an action based on the identified one or more differences.

Reducing churn rate for a social network service

Disclosed in some examples are methods, systems and machine readable medium for recommending an out-of-network communication by determining a set of potential recommended members of a social networking service based upon one or more recommendation criteria. In some examples the recommendation criteria may include: a profile similarity to a previous target of an out-of-network communication, a degree of correspondence between an interest and intent of the sending member, and a likelihood of response.

Suggested out of network communication recipients

The disclosed embodiments provide a system for processing data. During operation, the system obtains a first configuration for processing a first set of content items from a first data source and a second configuration for processing a second set of content items from a second data source. For each content item in the first set of content items, the system uses mappings from the first configuration to transform original fields from the content item into required fields in a record representing the content item. Next, the system generates, from the required fields, a document key for the content item. The system also performs deduplication of multiple records with the document key and stores a single record with the document key. Finally, the system uses the second configuration to generate, from the second set of content items, a set of records independently of processing the first set of content items.

Scalable processing of heterogeneous user-generated content

The disclosed embodiments relate to a system that uses data from an online social network to optimize subscription offers. During operation of the online social network, the system gathers data associated with subscription offers that were presented to members of the online social network, including information about which subscription offers were converted. Next, the system uses a machine-learning technique to train a model based on the gathered data. Finally, the system uses the trained model to select subscription offers to present to a member of the online social network.

Using data obtained from an online social network to optimize subscription offers

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San Jose, CA, United States of America

Yurong Shi