Microsoft Technology Licensing, LLC

Andrew James Wald

Marko Radmilac

Joshua Bryan Wyman Clemons

Rui Hu

Venkat Pradeep Chilakamarri

Wendy Guo

Jill Kathleen Larson

Noelle Renee Beaujon

A model comprises different processing nodes that perform different functions on input data, such as data prompts. Each node has batching criteria including a threshold value that when exceeded triggers a transmission of a batch of processing requests to the corresponding node. Different processing requests for a node are routed to a batching cache for that node. Processing requests are prevented from being routed to the node until the batching criteria is met. Once the batching criteria is met, a batch of processing requests stored in the batching cache are routed to the corresponding node.

Dynamic batching of prompt queries

A meta-model topology comprises a plurality of functions and conforms to a global label schema. A new function not included in the plurality of functions is integrated into the meta-model topology. A particular label of interest that is associated with the new function is identified and the new function is configured such that an output from the new function conforms to an output form corresponding to the particular label of interest from the global label schema. The new function is then integrated into the meta-model topology and the meta-model topology that includes the new function is used to generate a model graph. The model graph is then deployed to a remote application that is configured to receive data prompts comprising input data processed by nodes of the model graph.

Deployment of meta-model topologies and moderating graph generation

A contribution management system and process for facilitating the identification of individual users who have made contributions to an electronic content item, and the extent of that contribution. As an example, a reader may review the list of contributors with a representation of their relative degree or amount of contribution to the document, and also allow for access to other documents that have been developed by the identified contributor. These tools can provide collaborative document users the ability to more clearly distinguish casual contributors or non-contributing owners of the document from higher-level contributors whose authorship has significantly shaped the content. In addition, the listing or identification of top contributors can be configured to facilitate communication between an interested reader and the identified contributor, which increases the ease with which members of larger organizations can collaborate, seek mentorship, or develop useful relationships.

Document contribution management system

Systems and methods for providing productivity insights regarding user networks are provided. Productivity insights are determinable based on event data, such as email messaging events and/or calendaring events, and enable a user to see at a glance how and with whom the user has spent his or her time. Additionally, productivity insights highlight any changes that occur over time within a user network. Analytics based on event data allow a user to easily identify top collaborators, which may or may not be the most important collaborators, as well as specific metrics for each collaborator, such as response time, email read rate, total collaboration time, etc. Thus, productivity insights serve to qualify and quantify collaborative relationships for individual employees so that they can leverage their time more effectively by improving collaboration within their networks, thereby increasing workplace productivity.

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Bothell, WA, United States of America

Andrew James Wald