Microsoft Technology Licensing, LLC

Daniel Massey

Douglas Christopher Burger

Blaise Aguera Y Arcas

Bart J F De Smet

Andrew David Wilson

Michael F Cohen

Emmanouil Koukoumidis

Asta Jane Roseway

Saar Yahalom

Adam Edward Shirey

David Michael Sauntry

Mark A Groves

Donald Frank Brinkman, Jr

Ying Wang

Dustin Isaac Abramson

Qi Yao

Michael Andrews

Hudong Wang

Scott A Schwarz

Ian M Bavey

Kelli A Stuckart

Maria Alexandropoulou

Cezar Augusto Alevatto Guimaraes Neto

Blaise Hilary Aguera Y Arcas

Brian J Alseth

Richard P Lozada

Sergei Tuterov

Anthony Turner

Systems and methods for receiving various input data, processing said input data, and utilizing artificial emotional intelligence to analyze said input data to return calculated response stimuli are provided. Various electronic devices may be utilized to acquire input data related to a specific user, a group of users, or environments. This input data, which may comprise tone of voice, facial expressions, social media profiles, and surrounding environmental data, may be compared with past data related to a certain user, group of users, or environment. The systems and methods herein may employ artificial emotional intelligence to evaluate the aggregated data and provide a response stimulus to a user or group of users. The response stimulus may be in the form of uplifting/encouraging music, quotes, pictures, jokes, suggestions, etc. The purpose of providing the response stimuli is to significantly increase the productivity of meetings, conversations, and other interactions across electronic devices.

EQ-digital conversation assistant

A server device configured to execute an electronic data analysis platform program to store a plurality of modular data processing tools, each modular data processing tool configured to perform data processing with predetermined data types and to combine with other modular data processing tools in a data analysis pipeline, receive a user input of one or more user data sources, map the data of the one or more user data sources to one or more of the predetermined data types, determine a data analytic goal for the mapped one or more user data sources, select one or more modular data processing tools configured to process the one or more predetermined data types mapped to data of the mapped one or more user data sources to generate the data analytic goal, and generate a data analysis pipeline configured to generate the data analytic goal.

Modular electronic data analysis computing system

Systems and methods of a personal daemon, executing as a background process on a mobile computing device, for providing personal assistant to an associated user is presented. While the personal daemon maintains personal information corresponding to the associated user, the personal daemon is configured to not share the personal information of the associated user with any other entity other than the associated user except under conditions of rules established by the associated user. The personal daemon monitors and analyzes the actions of the associated user to determine additional personal information of the associated user. Additionally, upon receiving one or more notices of events from a plurality of sensors associated with the mobile computing device, the personal daemon executes a personal assistance action on behalf of the associated user.

Local personal daemon

Systems and methods for providing client-side integration of apps and services is provided. An integration framework execution upon a computing device provides integration of various apps, applications, services, sensors and the like. Upon receiving a request for a service, the integration framework accesses a registry of a plurality of services of a respective plurality of providers registered with the integration framework. Each of the services is registered with the integration framework is associated with a trust level of a hierarchy of trust levels. The integration framework iteratively searches the registry for a provider of the requested service according to the hierarchy of trust levels, beginning with the most trusted level of the trust levels to the less trusted trust level until a provider of the requested service is found or until all levels of the hierarchy are searched without finding a provider of the requested service.

Client-side integration framework of services

Systems and methods of a personal daemon, executing as a background process on a mobile computing device, for providing personal assistant to an associated user is presented. Also executing on the mobile computing device is a scheduling manager. The personal daemon executes one or more personal assistance actions on behalf of the associated user. The scheduling manager responds to events in support of the personal daemon. More particularly, in response to receiving an event the scheduling manager determines a set of apps that are responsive to the received event and from that set of apps, identifies at least a first subset of apps for execution on the mobile computing device. The scheduling manager receives feedback information regarding the usefulness of the executed apps of the first subset of apps and updates the associated score of each of the apps of the first subset of apps.

Incentive-based app execution

A system and method for facilitating analysis of a software project. Intrinsic measures, activity-based measures, or dynamic measures associated with the project are received, including measures associated with physical program units and logical program units of the project. Mappings between physical program units and logical program units are generated. An architectural diagram including logical program units is received, and may include additional mappings of the logical program units. The mappings are used to roll up measures from physical project units to logical project units, and from logical project units to other logical project units. An overlay diagram is generated, including the rolled up measures. The overlay diagram includes the architectural diagram and a representation of rolled up measures associated with each logical project unit on the diagram. The representations employ a graphic format that facilitates a user determining risk areas of the software project. A user may view effects of project changes prior to checking them into source control.

Architectural data metrics overlay

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Redmond, WA, United States of America

Daniel Massey