Microsoft Technology Licensing, LLC

Jingfeng Li

Walter Sun

Junaid Ahmed

Yan Ke

Jay Goyal

Yinzhe Yu

Lin Guo

Abhishek Kumar Singh

Florin Folta

Pratibha Permandla

Sasi Parthasarathy

Wei Zhuang

Vinay Deshpande

Alexander Coll

Paul Alexander Dow

Yajie Siamwalla

Hung-An Chang

Thomas Arthur Ledbetter

Brahm Kiran Singh

Venkat Sankepally

Subhojit Som

Ze Tian

Computer-readable media, computer systems, and computing methods for facilitating generation of entity names for entities are provided. The method includes determining a set of previously submitted queries that are associated with an entity. The most frequently used query within the set of previously submitted queries associated with the entity can be identified and, thereafter, designated as the entity name for the entity. The entity name can distinguish the entity from other entities. Such an entity name can be provided for presentation to a user, for example, as a related search suggestion via a search results page.

Generating distinct entity names to facilitate entity disambiguation

Methods, computer systems, and computer-storage media are provided for reference resolution. The present invention seeks to resolve entities in conversational search. To enable a more natural conversational search interaction, referential expressions such as pronouns are handled in queries. A component keeps track of previous queries and performs reference resolution based on an entity in the previous query and reformulates the query using an identifier for the referenced entity. Reference resolution may be performed for pronouns, plural pronouns, partial names, across domains, and on any device or platform.

Reference resolution

Methods, systems, and computer-readable media are provided for updating a search index with new uniform resource locators (URLs) and with metadata for new and known URLs. Data associated with communications made by users using a social network is received. The communications include a URL therein that a user has shared, posted, or otherwise communicated to one or more other users using the social network. When the URL is not found in a search index it is identified as a new URL and is added to the search index. A measure of a trending interest, or virality, of the URL is determined from the data. The determined virality is associated with the URL in a search index as metadata. The virality is useable to inform a ranking of the URL against a plurality of other URLs for identification and presentation as a search result in a search engine results page.

Using social-network data for identification and ranking of URLs

Methods, systems, and computer-storage media for improving the freshness, or the apparent freshness, of search results are described. In an embodiment, the first portion of search results presented on a search results page are based on responsiveness to the search query and a second portion of results describe only recently published documents that are responsive to the search query. In an embodiment, a more recent version of the document, which is not directly used to determine responsiveness, is used to build the caption for a search result. Another way to make search results appear fresh is to include a publication time within the search result caption. In one embodiment, the publication time is generated by calculating a point in time between when a document is first added to a search index and the previous time the search engine visited the site where the document was found.

Enhancing freshness of search results

Systems and methods for applying user behavior data to improve search query result ranking are provided. Upon receiving an update file indicating that recent, significant user behavior data is available for a document associated with an inverted index, the update file is published periodically and frequently to an index server. After filtering out the relevant update information from the update file, the index server extracts identifiers of the documents having the associated user behavior data. The update file and the identifier of the documents are utilized to update an in-memory index containing representations of metadata indicative of the user behavior. The in-memory index is continuously updated and utilized to serve search query results in response to user search queries. Search query results from the in-memory index are ranked using the user behavior data prior to serving. Thus, results associated with recent, significant user-behavior metadata receive prominent placement on the search results page.

Using behavior data to quickly improve search ranking

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Issaquah, WA, United States of America

Jingfeng Li