Microsoft Technology Licensing, LLC

Michael Victor Ehrenberg

George G Robertson

Jakob Peter Nielsen

William Guthrie Morein

William Henry Gates, Iii

Joshua T Goodman

Susan Theresa Dumais

Jensen Michael Harris

Danyel Aharon Fisher

Murali R Krishnan

Eran Megiddo

Brian Scott Ruble

Srikanth Shoroff

Jason Joseph Weber

Christian Bernd Schormann

Stella Yick Chan

Yanfang Shen

Joshua W Lee

Rekha Nanda

Nathan Paul McCoy

Gur Kimchi

Benjamin Edward Rampson

Bongshin Lee

Roland Lucas Fernandez

Richard J Wolf

Wolf Kohn

Brian L Welcker

B Scott Ruble

Kyle Stapley Young

Lisa Renee Mueller

Christian Olaf Abeln

Madan Natu

Sangram Salunkhe

Nitinkumar Shah

Sean Boon

Ramakanthachary S Gottumukkala

Cary Lane Rohwer

Daniel Christian Brown

Freddy Kristiansen

Morten Holm-Peterson

Josh W Honeyman

Barry James Givens

Nicholas Justin Lowe

Zelda B Zabinsky

Ahmed K Kamal

Sunil Garg

Daniel Schuster

Alvin Manalastas

Neil Gregory Huizenga

Thomas Emil Jensen

Malvika Malge

According to examples, an apparatus may include a processor and a memory on which are stored machine readable instructions that when executed by the processor, cause the processor to identify a plurality of tasks, identify a plurality of resources configured to execute the tasks, and decompose the plurality of tasks into multiple groups of tasks based on a plurality of rules applicable to the multiple groups of tasks. The instructions may also cause the processor to, for each group in the multiple groups of tasks, model the group of tasks and a subset of the plurality of resources as a respective resource allocation problem and assign a respective node of a plurality of nodes to solve the resource allocation problem.

Rules based decomposition of tasks for resource allocation

A set of SKUs is divided into a plurality of different Mean Field clusters, and a tracker (or sensor) is identified for each cluster. Product decisions for each Mean Field cluster are generated based on the tracker (or sensor) and each Mean Field cluster is then deconstructed to obtain product decisions for individual SKUs in the Mean Field cluster.

System forecasting and improvement using mean field

A system (and corresponding methodology) by which a user can interact directly with visual data is provided. The system employs associations and relationships between visual data objects to automatically update objects based upon a change in other objects. The innovation also provides specialized controls (e.g., dashboard tools/controls) that facilitate manipulation of visual data. As there can be numerous manners in which a user can interact with visualization data, the innovation enables a specialized set of controls to be identified and provided to a user thereby reducing overwhelming effects of a large number of controls.

Dashboard controls to manipulate visual data

A system facilitates dynamic data visualizations. The system includes an analysis component that periodically processes one or more incoming data streams to determine a visualization form from a plurality of visualization forms. A visualization component dynamically generates the visualization form based in part on the processing of the incoming data streams.

Visualization of streaming real-time data

A mobile computing device based expense capture and reporting system is provided. A mobile expense capture application is an integral part of a networked expense management service such as a Customer Relationship Management (CRM) or Enterprise Resource Planning (ERP) service. A user interface enables users to enter expense related information and accept/reject/edit prompted values for various entries. Upon completion of the entries, the information is transmitted to the networked service and/or stored locally. At least a portion of the information is automatically provided based on a location and/or action of the user. Furthermore, the mobile computing device is capable of capturing an expense document and retrieving at least some of the expense information from the captured document.

Mobile expense capture and reporting

Multiple pieces of information can be arranged into a single construct that allows the employee to ascertain information quickly while at her workstation. Selection of information for placement into the construct can employ various statistical models and the like. Selective pieces of information can be masked for a user's construct based upon access rights of the user. Constructs can be configured by a user based on personal preferences as well as by an administrator. Population of metadata upon the construct can be performed automatically through an instruction of the administrator or be overridden by a user request. In addition, various types of synchronization can be implemented between constructs, such that identical or near-identical information is populated upon multiple constructs.

Communication workspace

Providing for generation of a task oriented data structure that can correlate natural language descriptions of computer related tasks to application level commands and functions is described herein. By way of example, a system can include an activity translation component that can receive a natural language description of an application level task. Furthermore, the system can include a language modeling component that can generate the data structure based on an association between the description of the task and at least one application level command utilized in executing the computer related task. Once generated, the data structure can be utilized to automate computer related tasks by input of a human centric description of those tasks. According to further embodiments, machine learning can be employed to train classifiers and heuristic models to optimize task/description relationships and/or tailor such relationships to the needs of particular users.

Providing a task description name space map for the information worker

Management of metadata applied to life cycle inventory (LCI) and life cycle assessment (LCA) data is provided. Life cycle inventory data may be provided through a secure framework to a data hub where it may be validated and audited and where the received life cycle inventory data may ultimately be used to generate a life cycle assessment score for a given product. Life cycle inventory data may be provided via a structured data template provided by a supplier or obtained by a supplier via a requested unit business process model. Metadata may be applied to each LCI data item to allow the data items to be stored, sorted, search, retrieved and used for validating and auditing the data and for comparing the data to other data items of similar data types for eventual use in the generation of the aforementioned life cycle assessment score for a given product.

Management of metadata for life cycle assessment data

A visualization development system is provided. The system includes a visualization tool to develop one or more visualizations and a grammar engine that operates with the visualization tool to automatically detect visualization problems during the development of the visualizations.

Grammar checker for visualization

The location of a drawing of an activity, a property of an element in the drawing and the structural relationship of elements in the drawing are stored in a database. The database is accessed to form a user interface that provides a hierarchical representation of activities and the elements within activities.

Creating, storing and viewing process models

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Seattle, WA, United States of America

Michael Victor Ehrenberg