Microsoft Technology Licensing, LLC

Deqing Chen

Yan Ke

Dmitry V Zhiyanov

Michel Naim Naguib Gerguis

Eslam Kamal Abdel-Aal Abdel-Reheem

Sayed Hassan Sayed Abdelaziz

Yuval Yehezkel Marton

Ahmed Mohamed Emad Morsi Abdelbaki

Brandon Robert Anderson

Krysta Marie Svore

Lucretia Henrica Vanderwende

Chenguang Yang

Achraf Abdel Moneim Tawfik Chalabi

Mahaveer Bhavarlal Kothari

Jamil Valliani

Susan Elizabeth Sullivan

Achraf Abdel Maneim Tawfik Chalabi

A system and method for identifying relevant content from other documents and presenting candidate documents in a document authoring application is described. The system identifies a pattern of events from the document authoring application. The system receives a request to identify candidate documents pertinent to a document present in the document authoring application. A set of candidate documents is identified from a document library based on the pattern of events, a reuse score for each candidate document, a similarity score for each candidate document, and content in the document present in the document authoring application. The set of candidate documents is provided in a user interface element of the document authoring application.

System for predicting document reuse

A computer-implemented technique is described herein for extracting facts from unstructured text documents provided by one or more information sources. The technique uses a pipeline to perform this operation that involves, at least in part, providing a corpus of information items, extracting candidate facts from the information items, merging synonymous argument values associated with the candidate facts, organizing the candidate facts into relation clusters, and assessing the confidence level of the candidate facts within the relation clusters.

Extracting facts from unstructured information

Methods, systems, and computer-storage media having computer-usable instructions embodied thereon for identifying related entities are provided. One or more entities may be identified from a search query. The one or more entities may include any identifiable term having related information associated therewith. An entity store may be referenced to identify one or more related entities related to the entity. The one or more related entities, along with their relationship(s) to the entity (and one another, perhaps) may then be ranked and displayed to a user.

Identifying related entities

Methods and computer-readable media are provided for summarizing the content of a plurality of documents and presenting the results of such multiple-document summarization to a user in such a way that the user is able to quickly and easily discern what, if any, unique information each document contains. Each sentence of each document is assigned a score based upon the perceived importance of the information contained therein. The sentences receiving the highest scores are then compared with one another to identify and remove any duplicate sentences. The remaining high-scoring sentences are extracted from the corresponding documents and presented to the user, for instance, in a bulleted list format. The user can then simply scan the list and can quickly and easily discern the unique information contained in each document.

Presenting multiple document summarization with search results

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Issaquah, WA, United States of America

Deqing Chen