Microsoft Technology Licensing, LLC

Stefan Debald

Ashok Kuppusamy

Oleg Melnychuk

Manfred Nysted Berry

Andreas Eide

Lucian Baciu

Ivan Dijan

Marius Tennoe

Sangram Jyoti Bal

Alexander J Pope

Robin Miller

Dmytro Baglai

Janaka C Perera

Fredrik Holm

Joshua Stickler

Bjørnstein Lilleby

Viral Shah

Rune Devik

Manolis Platakis

Thanuja Priyadarshani

Øyvind Linna Eikeland

Mathuranthagaa Selvarathnam

Marcin Łukasz Roman

Colamba Patabedige Janaka Chathuranga Perera

Context and social distance aware fast live people cards are described. A user context and/or a relevant person context may be determined in response to detecting a user interest in viewing contact information. The user context may include user's attributes such as organizational position, preferences, location, working hours, which application the user is employing, etc. Relevant person context may include context information (similar to the user's) for people within a predefined social distance such as the user's peers, supervisor(s), close friends, etc. Information associated with one or more persons of interest to the user may then be selected and retrieved from a cache storage at a server a productivity service to be provided to a client application for display to the user. Information to be stored in server cache for rapid retrieval may also be selected based on user and relevant person context using observed user behavior.

Context and social distance aware fast live people cards

When content is shared, the sharer of the content is identified, as are the audience members. An entry is generated in a data store that identifies the content, the sharer and the audience members. Content retrieval requests can then be processed against the data store to identify and return content.

Retrieval of enterprise content that has been presented

A personalized view of insights into social activity surrounding a content item is provided that may indicate to a user why a given piece of content may be interesting to him/her. A user's activities, as well as the activities of others (e.g., colleagues of the user) may be shown, including such items as a total number of views, comments, followers, and likes associated with the content item. The insights view may be personalized based on the user's relationships with other users in association with the content item. The user may learn through the personalized view who among his/her relationships have commented, edited, shared, or liked the content item, as well as, how many of the user's colleagues have viewed the content item. In addition, through a search function that may be applied to the view content, a user may learn about related content items based on the social insights.

Displaying and posting aggregated social activity on a piece of enterprise content

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Oslo, Norway

Stefan Debald