Microsoft Technology Licensing, LLC

Haiyang Liu

Birjodh S Tiwana

Jesse Jyh-Cherng Hsia

Shaunak Chatterjee

Mark Hull

Arpit Dhariwal

Kinjal Basu

Christopher Szeto

Siva Visakan Sooriyan

Sammy Shreibati

Vivian Mak Urata

Kurt Mcculloch

Qianru Zhang

Michael Joshua Aft

Described herein is a contextual contact recommendation or suggestion service and system. The service, which, in some embodiments, is integrated with a social networking service and/or an instant messaging service, takes as input a first parameter that identifies a member of the social networking service, and a second parameter that defines a context (e.g., a web page that is being viewed by the member. The service, based in part on the context, computes a ranked list of members to populate a contextual contact list, thereby recommending or suggesting contacts, with whom the member might be interested in initiating, or continuing, a conversation, based on the context of the member's current web browsing session. Optionally, the service may take as input a third parameter, defining a use case, such that the recommendation algorithm can be customized by use case.

Techniques for presenting a contextual contact list

Described herein is a technique to facilitate the sharing of a content item presented in a content feed of a social networking service. Upon detecting that a member has selected an option to share a content item, a content sharing interface is presented. The content sharing interface includes options share the content item publically via a content feed, and privately via a messaging service. The content sharing interface provides a ranked list of recommended recipients, where the recommended recipients in the list are selected and ordered based on several factors, including factors relating to the relationship between the sharing member and the recommended recipients, as well as factors relating to the subject matter of the content item and the likelihood that a recommended recipient would be interested in the content item.

Sharing content to multiple public and private targets in a social network

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Redwood City, CA, United States of America

Haiyang Liu