Microsoft Technology Licensing, LLC

Rune Devik

Dag Steinnes Eidesen

Adrian Fanaru

Darrin N Hatakeda

John D Fan

Fredrik Holm

Krister Mikalsen

Gunnar Ljosdahl Rasmussen

Bjornstein Lilleby

Ashok Kuppusamy

Michael James Taylor

Torbjørn Helvik

Bård Kvalheim

Vidar V Vikjord

Viral Shah

Bjørnstein Lilleby

Joshua Stickler

Torbjorn Helvik

Øivind Wang

Stefan Debald

Håkon Bergland Brugård

Azmil Macksood

Sangram Jyoti Bal

Magnus Mortensen

Erlend Jensen

Robin Miller

Øyvind Linna Eikeland

Mathuranthagaa Selvarathnam

Marcin Łukasz Roman

Colamba Patabedige Janaka Chathuranga Perera

Roshan Gamage

Stein Arild Jakobsen

Hakon Brugard

Roger Hansen

An analysis application utilizes interactivity signals to generate relationships and promote content. One or more interactivity applications, such as a social networking application, are queried to retrieve interactivity signals. Interactivity signals include an interaction pattern that indicates a relationship between a user and relations of the user. A relationship graph is constructed based on the interactivity signals. Content associated with a user is promoted based on the relationship graph. A weight of the interactivity signals is adjusted to improve a ranking of the relationship graph and a ranking of the content.

Utilizing interactivity signals to generate relationships and promote content

Collected usage information relating to interaction with content is integrated with operation of a system, such as a content management system. The usage information is collected in response to occurrences of usage events. A user may create, configure and define the usage events according to their needs. The user may also configure/define different values that are associated with the different events. For example, a user may specify: when to count a view (e.g. unique user view or each view); what period of time to collect counts; aggregation of counts (e.g. tenant, site, collection); a weighting for the event; a trim value; when to provide the parameter to a search index of the system such that the value is considered by the search engine of the system; whether or not a parameter is configurable by other users, and the like.

Extensibility model for usage analytics used with a system

Configuring usage events that affect analytics of usage information

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

A computer-implemented method that monitors the activity of different nodes within a system as well as crowd sourcing activity. The computer-implemented method determines that a first node formed a relationship with a second node, generates an edge based on the relationship between the first node and the second node, stores the edge in a graph index and assigns a privacy setting to the edge based on the relationship between the first and second nodes.

Access control of edges in graph index applications

Growing community of inventors

Tromso, Norway

Rune Devik