Microsoft Technology Licensing, LLC

Microsoft Corporation

Evelyne Viegas

Henricus Johannes Maria Meijer

Stephen Harris Toub

Saliha Azzam

David Neal Weise

Patrick Pantel

Kevin Roland Powell

Michael V Calcagno

Sonja Sabina Knoll

Karin Breitman

Pär Jonas Barklund

Eric Anthony Rozell

Savas Parastatidis

Varish Mulwad

David N Weise

Kevin R Powell

Sonja S Knoll

Described herein are technologies pertaining to automatically summarizing contents of a dataset and visualizing a summary of the dataset together with summaries of other datasets. A schema that defines the structure and content of a dataset is received, and pre-processing is undertaken on the schema to generate an enriched schema. Portions of the enriched schema are selected to generate a semantic summary of the schema, which is included with at least one exemplary entry of the dataset to generate a summary of the dataset.

Semantic search interface for data collections

Among other things, one or more techniques and/or systems are provided for building an action catalogue, generating an action frame for an action within the action catalogue, and/or executing an action. In an example, an action may be included within the action catalogue based upon descriptive text associated with an application indicating that the application is capable of performing the action (e.g., a movie app may be capable of performing an order movie tickets action). A parameter (e.g., a movie name) and/or an execution endpoint (e.g., a uniform resource identifier used to access movie ticket ordering functionality) may be used to generate an action frame for the action. In this way, user intent to perform an action may be identified from user input (e.g., a spoken command), and the action may be performed (e.g., on behalf of the user with minimal additional user input) by using the action frame.

Action broker

Technologies pertaining to retrieval of contextually relevant attribute values for an automatically identified named entity in a document are described herein. Named entity recognition technologies are employed to identify named entities in the text of a document. Context corresponding to an identified named entity is analyzed to probabilistically assign a class to the named entity. Attributes that are most relevant to the class are determined, and attribute values for such attributes are retrieved. The attribute values are presented in correlation with the named entity in the document responsive to user-selection of the named entity in the document.

Enrichment of named entities in documents via contextual attribute ranking

A technique for protecting the privacy of a query is provided using permissions that may be derived from an analysis of the context of the query. A monitoring component can be provided to receive or intercept queries directed at a datastore, and a privacy component is provided that analyzes permissions associated with the queries. The privacy component can also determine access levels of the queries based on the analysis of the permissions. A response component can then be provided to answer the queries in accordance with the access levels of the queries.

Permission based query processing

The present invention is a named entity (NE) interface to a linguistic analysis layer. The interface exposes each input sentence to the NE recognizers of all applications and returns all recognized NEs. Thus, the present invention can accommodate NEs which dynamically change in the applications, because each input string will be handed to the applications for NE recognition. The present invention also includes a data structure which is a normalized form of recognized NEs.

Named entity (NE) interface for multiple client application programs

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Redmond, WA, United States of America

Evelyne Viegas