Microsoft Technology Licensing, LLC

Nitin Agrawal

Hugh Evan Williams

Sanaz Ahari

Tabreez Govani

Jamie Paul Buckley

Michael Maxwell Cameron

Yang Yang Zhang

Nipoon Malhotra

Srinath Reddy Aaleti

Liwei Chen

Nicholas Eric Craswell

Milad Shokouhi

Kenneth Alan Moss

Christopher A Meyers

Kieran Richard McDonald

Andy Lam

Song Zhou

Ye-Yi Wang

William Ramsey

Vipindeep Vangala

Gopi Prashanth Gopal

Omar Zia Khan

Gaurav Sareen

Ran Gilad-Bachrach

Brian W MacDonald

Bo-June Hsu

Nikhil Dandekar

Shobana Balakrishnan

Farid Hosseini

Robert A Williams

Pankaj Khanzode

Filip Andrzej Radlinski

Derrick Leslie Connell

Xin Liu

Maxim V Stepin

Nick Craswell

Amir Jonatan Padovitz

Andrew Peter Oakley

Jay Goyal

Krishna Chaitanya Gade

Timothy C Hoad

James Francis Gilsinan, Iv

Kumaresh Pattabiraman

Neil Sharman

Antonio Gulli

Tapas Kanungo

Muhammad Aatif Awan

Nicholas Craswell

Amit Aggarwal

Jason A Bolla

James Brian Lawson

Bodo Billerbeck

Mairéad Áine O'Donovan

Kimberly M Vlcek

Natalia Burina

Hemant Banavar

Simant Dube

Binit Kumar Jha

A computer-implemented technique is described herein for creating a relational data structure by extracting user data items from a collection of one or more applications sources. These data items evince interests exhibited by the users, and may include messages, documents, tasks, meetings, etc. The technique also collects knowledge data items from one or more knowledge sources. In one implementation, these data items may include terms used to describe skills possessed by the users. The technique constructs the data structure by providing objects associated with respective data items, and links between respective pairs of objects. In its real-time phase of operation, the technique allows a user to interrogate the relational data structure, e.g., to identify skills possessed by a particular user, to find users associated with a specified skill, etc.

Querying a relational knowledgebase that provides data extracted from plural sources

Systems, methods, and computer-readable storage media for providing query-completion suggestions configured to be searched against vertical information domains in response to receiving a general web search query are provided. At least a portion of a general web search query is received. As the portion of the general web search query is received, query-completion suggestions are determined as is a likely primary intent associated with at least a portion of the determined query-completion suggestions. If the likely primary intent associated with a particular query-completion suggestion is for information associated with a particular vertical information domain other than the general web domain, the query-completion suggestion is provided such that selection thereof causes searching of the query-completion suggestion against the particular information domain for search results.

Domain specific query-completion suggestions

Methods, computer-storage media, and graphical user interfaces are provided for identifying and presenting rich related sites for task-oriented search queries. Upon receipt of a search query input by a user, one or more query logs are analyzed to determine if the search query is a related to a task being performed by the user. If the query is determined to be a task-oriented search query, search results are identified, as is one or more Uniform Resource Locators (URLs) related to a particular search result. The related URL is presented to the user in association with the particular search result. Additional controls, e.g., search tools that facilitate querying of those URLs determined to be relevant to a particular search result, may also be provided to aid the user in performing the task at hand.

Related URLs for task-oriented query results

Various embodiments of the disclosed subject matter include computer-implemented methods, computer-readable media, and computer systems configured to respond to a search query from a computer user. In response to receiving a search query from the computer user, search results are obtained. A plurality of user intents are identified according to the obtained search results. The obtained search results are then grouped according to the subject matter of the search results, where each group corresponds to one of the plurality of user intents. A first user intent (with the corresponding group of search results) is selected. A search results page is generated from the search results of the group the search results corresponding to the selected first user intent and the generated search results page is returned to the computer user in response to the search query.

Intent-based presentation of search results

A system and method are provided for detecting entity information contained within search results. The detected entity information can be used to determine a category of entity as well as a specific entity within the search results. Entity information can be extracted from the documents associated with the search results. This information can be used as part of the information for an entity card, which can be displayed to a user in conjunction with and/or in place of the search results.

Entity detection and extraction for entity cards

Systems, methods, and computer-readable media for determining the Internet search popularity of an entity are provided. Embodiments of the present invention include receiving a group of Internet search records and assigning a popularity ranking based on the number of times an entity descriptor associated with an entity occurs within the group of Internet search records created over a designated time period. An entity descriptor is one or more terms commonly used to identify an entity. The trend in an entity's popularity rank may also be calculated. An entity's popularity rank and trend in popularity rank may be presented in a graph or in a list.

Determining entity popularity using search queries

The present invention is directed to presenting a suggested search query. Responsive to receiving a user-devised search parameter, a suggested search query is identified. The user-devised search parameter might have been previously received by a search system, or alternatively, might be a unique query that has not been previously received. A suggested search query might be generated using various techniques, such as by applying an n-gram language model. A classification of the suggested search query is determined, and the suggested search query is presented together with a visual indicator, which signifies the classification.

Generating and presenting a suggested search query

Technologies are described herein for placing search results on a search engine results page (SERP). A query may be received. The query may be transmitted to a plurality of search result providers. A first set of search results and a second set of search results may be received from the search result providers. Intent features may be extracted from the first set of search results. User intent of the second set of search results may be inferred based on the extracted intent features. The first set of search results and the second set of search results may be ranked based on the inferred user intent. The SERP may be rendered according to the ranked first set and second set of search results.

Placement of search results using user intent

A computer system, method, and media for associating locations with ranked websites are provided. The computer system includes a search engine, a log database, and a location database that are employed to respond to search requests from users by returning appropriately ranked websites to the user. The websites are ranked using the location of the website and the location of the user to select websites to receive high ranks. Additionally, the search engine includes a correction feature that reevaluates locations for a website or user when a large number of obtained locations suggest a different location than a currently associated location for the website or the user.

Promoting websites based on location

Methods and computer-storage media having computer-executable instructions embodied thereon that facilitate generating a machine-learned model for ranking search results using click-based data are provided. Data is referenced from user queries, which may include search results generated by general search engines and vertical search engines. A training set is generated from the search results and click-based judgments are associated with the search results in the training set. Based on click-based judgments, identifiable features are determined from the search results in a training set. Based on determining identifiable features in a training set, a rule set is generated for ranking subsequent search results.

Ranking search results using click-based data

A method, system, and medium are provided for enhancing a search result snippet that is associated with a URL. Potentially descriptive terms of the URL are identified by reconciling multiple sources of terms related to the URL. One aspect includes comparing search terms of historically relevant queries to anchor text for the URL. The search result snippet might be intelligently enhanced by causing common terms to be visibly distinguished when the snippet is displayed.

Intelligent enhancement of a search result snippet

Methods and computer-readable media are provided for displaying a target search result and relevant information on a search results page in response to a user-inputted query on a search page. The target search result and relevant information are identified in a database as having been previously determined to be most relevant to the query, and may be based on past user behavior, for example. The relevant information may include functional tools that include input boxes allowing for the user to interact with a webpage associated with the target search result via the search results page. Once the target search result and relevant information have been determined, the search results page is displayed.

Providing tools for navigational search query results

Growing community of inventors

Redmond, WA, United States of America

Nitin Agrawal