Microsoft Technology Licensing, LLC

Yahoo! Inc.

Yiping Zhou

Yi Li

Kang Li

Zhengdong Lv

Yohn Cao

Lance Alan Riedel

Robert J Collins

Gianluca Donato

Aparna Rajaraman

Shaji Sebastian

Oana Nicolov

Graham Harris

Jesse Harris

Grant Kushida

Mohammad Sabah

Jeff Yuan

Architecture that enables the extraction of document-specific salient terms from documents for use improving the result summaries on a search engine result page (SERP), and methods to extract the salient terms from the documents using search engine logs, document metadata, and other algorithms. Document-specific salient terms can provide additional information and significantly improve user success in finding relevant documents while disregarding non-relevant documents. The architecture also enables the extraction of entity information from a variety of sources, some of which are at a query level, and other sources that are specific to a single document. All the entities available are aggregated for a set of results and the most relevant results are identified. The final set of results is then used to determine where in the document summary to apply visual emphasis or cues (e.g., bolding).

Salient terms and entities for caption generation and presentation

An entity-based search system is described herein that detects and recognizes entities in Internet-based content and uses this recognition to organize search results. The system associates one or more entity identifiers with a web page and stores this information as metadata of the page in a search engine index. This metadata will enable entity-based queries as well as rich data presentations in a search engine result page (SERP), including grouping results by entities, filtering results by one or more particular entities, or re-ranking search results based on user preference of entities. Thus, the entity-based search system allows users to identify a particular entity the user is interested in finding, and to receive search results directly related to that entity.

Knowledge-based entity detection and disambiguation

The present disclosure is directed to systems and methods for determining semantically related terms. Generally, one or more seed terms are received from a user. A system searches a first index comprising a plurality of terms and one or more webpages associated with each term of the plurality of terms to determine a plurality of webpages associated with the seed terms. The system then searches a second index comprising a plurality of webpages and one or more terms associated with each webpage of the plurality of webpages to determine a plurality of potential terms associated with the plurality of webpages associated with the seed terms. At least one term of the plurality of potential terms is suggested to a user.

System and method for determining semantically related terms

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Sunnyvale, CA, United States of America

Yiping Zhou