Microsoft Technology Licensing, LLC

Textio, Inc.

Robert Emmett Kolba, Jr

Max Glenn Morris

Sandy Wong

Daniel Oliver

Sashi Raghupathy

Manoj Kumar Biswas

Amy Harilal Rambhia

Jensen Michael Harris

Kieran Snyder

Lawrence Fubini Waldman

Gaurav S Anand

Thomas Charles Underhill

Shajib Sadhukha

Voicu Anton Albu

Liwei Chen

Scott Harrison Douglas

Benjamin David Langmaid Stewart

Melitta Lorraine Geistdoerfer Andersen Riley

An action framework system provides context-based actions in association with a source application. The source application detects selection of a content element presented by the source application. The content element is associated with an application identifier identifying a target application and an action identifier identifying an operation to be executed by the target application on the content element. The target application identified by the application identifier is executed to perform the operation identified by the action identifier on the content element, responsive to detection of the selection of the content element. In one implementation, the source application is a search feature providing different contexts of search results (e.g., from a local file system search, a local application content search, a Web search, a remote application content search).

Context-based actions from a source application

Evaluations of a document are generated that indicate likelihoods of the document achieving its objectives. The evaluations are based on predictive characteristics of one or more outcomes of the client document that are indicative of whether the document will achieve its objectives. Specifically, a server receives the document from a client device. The server extracts a set of features from the document. The evaluations of the document are generated based on the predictive characteristics for the one or more outcomes of the document. The generated evaluations are provided to the client device such that the document can be optimized to achieve its desired objectives. The optimized document may also be sent to a posting server for posting to a computer network. The known outcomes of the optimized document are collected through reader responses to the document and analyzed to improve evaluations for other documents.

Using machine learning to predict outcomes for documents

A search service executes on one or more computing systems and searches at least one index associated with content accessible through an application based on the at least one portion of the search query to provide search results associated with the application. A search results interface returns one or more search results from the search. At least one of the search results is associated with an application identifier identifying the application. The search service ranks the search results associated with the application with other search results from at least one other search of other content based on the search query.

Search result contexts for application launch

Technologies are described herein for creating and editing dynamic graphics via a World Wide Web ('Web') interface. A Web service is provided for generating dynamic graphics in response to requests received from client computers. In response to requests from client computers, the Web service generates requested dynamic graphics and returns the generated dynamic graphics to the client computers in response to the requests. Parameters may be provided to the Web service indicating a list of text items, a layout type, a visual style, a color, and other aspects of a dynamic graphic. A user interface is also provided for creating and editing a dynamic graphic within a Web browser application.

Creating and editing dynamic graphics via a web interface

An application program utilizes a decoding sub-system and a three-dimensional (3D) rendering sub-system to apply effects to a video in-place in a document. The program configures pixel shaders for use with a rendering device for applying pixel-level effects to the decoded frames of the video, generates meshes, and pre-renders textures for use in implementing effects. When a request is received to play back the video in-place in the document, a decoding surface and a rendering surface are allocated. The decoding sub-system decodes frames of the video and copies the decoded frames to the decoding surface on one thread. A separate thread copies decoded frames from the decoding surface to a texture and from the texture to the rendering surface. The rendering device utilizes the pixel shaders, meshes, pre-computed textures, and other data to render the frames of the video to a rendering target.

Applying effects to a video in-place in a document

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Seattle, WA, United States of America

Robert Emmett Kolba, Jr