Microsoft Technology Licensing, LLC

Eduardo D Melo

Zohaib Haider Ali

Hayley Lynn Steplyk

Yamin Wang

Elena Catrinescu

Joseph Marcus

Michael Brickman

Chao Wang

David Paul Limont

Selvaraj Nalliah

Zhen Wang

Srinivasa Reddy Manda

Thomas W Millett

Russell L Simpson, Jr

Xin Li

Christian Piccolo

Kevin Christopher Clement

Sirish Kumar Balaga

Mihir S Ray

David Meyers

Samuele Carpineti

Jiaojiao Li

Tao Zhang

Yapu Jia

Ziqiang Liu

Xiao Hu

Lu Zhang

Edward T French

Saif R Hasan

Peng Wang

Lve Chen

Yueyang Wang

Bryan K Walton

Cheryl A Evans

Frank M Sager

Chunyu Li

Chunyu Liu

Ang Lv

Tong Wang

Xiaocheng Zhou

The present disclosure provides a technical solution related to tagging user behavior data. The processing device and method may determine and tag user behavior data according to an application to which the user behavior data belong based on analysis on an inheritance relationship between tasks associated with the user behavior data, so as to facilitate selectively deleting the user behavior data later.

Tagging of user behavior data

Various parts of email content or entire emails may be recalled or modified after delivery through the use of links to cloud-storage, where the various parts of the email content may be stored. Different notification and modification methods may be employed to modify delivered content even after it is rendered for a recipient. While recipients may have a latest version of the email content, senders may be enabled to see a version history of changes in delivered email content.

Modification of delivered email content

Variety of approaches to optimize performance based on behavioral and situational signals are described. A productivity service initiates operations to optimize performance upon receiving a behavioral signal and/or a situational signal associated with a user. The behavioral signal and/or the situational signal are analyzed to infer a usage pattern associated with a component of an application. Next, a failure of the usage pattern is detected in a comparison to an utility threshold. In response, the application is instructed to interrupt an execution of the component.

Optimizing performance based on behavioral and situational signals

Described herein are one or more implementations facilitating the extensibility of a tool for configuration and management of server-functionality role(s) of a network server. One or more implementations, described herein, provide an extensibility model that allows additional server-functionality roles to be included in the list of user-selectable server-functionality roles available on a server. When selected by user, the model enables management and configuration of the additional server-functionality roles.

Server-functionality role extensibility model

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Redmond, WA, United States of America

Eduardo D Melo