Microsoft Technology Licensing, LLC

Other

Google Inc.

Sanaz Ahari

Nitin Agrawal

Michael Maxwell Cameron

Brian W MacDonald

Farid Hosseini

Hugh Evan Williams

Liwei Chen

Tabreez Govani

Sarthak D Shah

Nikhil Dandekar

Yang Yang Zhang

Jamie Paul Buckley

Xiaoxin Yin

Srinath Reddy Aaleti

Adam D Troy

Jianfeng Gao

Paul A Viola

Xiaodong He

Li Jiang

Daniel Marantz

Milad Shokouhi

Derrick Leslie Connell

Nipoon Malhotra

Alnur Ali

Kieran Richard McDonald

Timothy C Hoad

Bodo Von Billerbeck

Dan Fain

Oren Eli Zamir

Milind V Mahajan

Gopi Prashanth Gopal

Ahmad A Abdulkader

Amit Kumar

Peter Bailey

Gaurav Sareen

Ran Gilad-Bachrach

Steven William Macbeth

Bo-June Hsu

Girish Kumar

Paul Ronald Ray

Robert A Williams

Mira Lane

Filip Andrzej Radlinski

Samir Shiraz Pradhan

Maxim V Stepin

Rodney Coleman Edwards

Deepak Vijaywargi

Andrew Peter Oakley

Nick Craswell

Troy L Walker

Jay Goyal

Ankur Gupta

Christopher A Meyers

Radoslav M Kirov

Neil Sharman

Andrew Paul McGovern

Gregory T Buehrer

Yatharth Saraf

Steven Tullis

Mehdi Sharifzadeh

Muhammad Aatif Awan

Nicholas Craswell

Jason A Bolla

Steve Macbeth

Alec John Berntson

Vijay Nair

Dan Blandford

Song Zhou

Daniel C Fain

Laura Kern

Jeffrey R Kelleran

Muhammad Arif Iqbal

Nazan Khan

Giridhar Kumaran

Bodo Billerbeck

Jeff Bergman

Jakub Jan Szymanski

Methods, systems, and apparatus include computer programs encoded on a computer-readable storage medium for measuring lift. A method includes: receiving requests for content for which a first content item is an eligible content item; delivering the first content item along with a first pixel that identifies the delivery of the first content item to a first portion of the received requests; delivering a second, different content item along with a second pixel that identifies the non-delivery of the first content item to a second portion of the received plurality of requests rather than the first content item; evaluating searches performed by users that received the first content item as compared to users that received the second content item including using the first pixel and second pixel in evaluating search logs associated with search requests performed by users; and presenting lift data to a sponsor associated with the first content item.

Measuring search lift resulted by online advertisement

Computer-readable media and computerized methods are provided for identifying terms associated with one or more queries, including aspects directed to manipulating a list of terms associated with a query class by extracting terms, identifying equivalences or relevant terms, and condensing or expanding the list of terms. In embodiments, synonymous terms can be identified. An updated list of terms can be written to a storage location in association with a query or query class.

Identifying terms associated with queries

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

Systems, methods, and computer media for identifying related strings for search query rewriting are provided. Session data for a user search query session in an accessed click log data is identified. It is determined whether a first additional search query in the session data is related to a first user search query based on at least one of: dwell time; a number of search result links clicked on; and similarity between web page titles or uniform resource locators (URLs). When related, the first additional search query is incorporated into a list of strings related to the first user search query. One or more supplemental strings that are related to the first user search query are also identified. The identified supplemental strings are also included in the list of strings related to the first user search query.

Enhanced query rewriting through click log analysis

Systems, methods, and computer media for enhancing search results, as well as user interfaces for performing search queries and navigating search results, are provided. A search query is received from a user. A plurality of web pages relevant to the search query are identified. At least one of the relevant web pages is identified as popular. A search result page is generated including a search result listing and a search result page header. The search result page header includes a link to the popular web page to provide the user with a quick and easy way to select a popular web page relevant to the user's search query.

Navigation to popular search results

Systems, methods, and computer-readable storage media for providing task-oriented query-completion suggestions are provided. A portion of a search query is received, for instance, via a query-input region or search box presented in association with a general web search domain. As the portion of the search query is received, it is determined that the received search query portion is suggestive of a task-oriented user intent. Also determined are query-completion suggestions that are associated with the task-oriented user intent of which the search query portion is suggestive. The determined query-completion suggestions are then provided to the user. As query-completion suggestions are surfaced with input of short character sequences that are associated with task-oriented user intents, users can quickly be provided the relevant, rich content for completing their intended tasks.

Task-oriented query-completion suggestions with shortcuts

Computer-readable media, computer systems, and computing devices for facilitating presentation of search result items having varying prominence is provided. The method includes referencing a search result item to be presented within a search results page in response to a search query. Thereafter, a determination is made that a size prominence of the search result item is to be modified. Such a determination can be based on a result attribute(s) associated with the search result item and a result attribute(s) associated with other search result items within the search results page. The size of the search result item is adjusted in accordance with the determination that the size prominence of the search result item is to be modified.

Presenting search result items having varied prominence

Techniques are described herein for processing social search results. Such social search results may be included in a relatively higher-ranked (e.g., a highest-ranked) subset of a user's search results and/or selected from a relatively lower-ranked subset of the user's search results in response to a determination that the relatively higher-ranked subset includes social search result(s). In one example, the social search results (or a subset thereof) may be annotated to include publicly available rich metadata. Such metadata may be extracted from user profiles on social networking domains from which the social search results are received. In another example, the social search results (or a subset thereof) may be clustered such that they are consecutively ranked. In yet another example, the social search results (or a subset thereof) may be configured to be displayed in a designated arrangement (e.g., in a grid having multiple columns).

Processing social search results

Computer-readable media, computer systems, and computing methods are provided for classifying search results as either of good quality or of poor quality. Initially, a portion of the search results, such as the highest ranked documents, are selected for evaluation. A level of quality for each of the selected search results is determined using a classification process that includes the following steps: targeting features demonstrated by the selected search results to be evaluated; evaluating the selected features to generate a level-of-quality score for each of the selected search results; comparing the score against a predefined threshold value; and, based on the comparison, assigning each of the selected search results an absolute measurement. The absolute measurement indicates poor quality when the score is less than the threshold value. Upon recognizing that the selected search results are of poor quality, automatically executing a corrective action that reformulates the issued search query.

Classifying results of search queries

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

Methods, systems, and media are provided for facilitating generation of an inference index. In embodiments, a canonical entity is referenced. The canonical entity is associated with web documents. One or more queries that, when input, result in a selection of at least one of the web documents are identified. An entity document is generated for the canonical entity. The entity document includes the identified queries and/or associated text from the content of a document or from an entity title that result in the selection of the at least one of the web documents. The entity document and corresponding canonical entity can be combined with additional related entity documents and canonical entities to generate an inference index.

Inference indexing

Computer-readable media, computer systems, and computing devices facilitate providing a comparison experience to a user in response to a search query. Upon receiving a search query from the user, entities are extracted from the query. The entities are associated with entity classes. The entities, entity classes, previous user behavior, and other information are used to infer whether the user likely is engaging in a comparison task. If the inference indicates that the user likely is engaging in a comparison task, a comparison experience is generated and access to the comparison experience is provided to the user.

Providing comparison experiences in response to search queries

Computer-readable media, computer systems, and computing methods are provided for implicitly discovering applications using a query or search results, where the query does not explicitly target a particular application. A search engine is used to receive a user-initiated query and to employ a keyword of the query to generate an initial set of search results. Characteristics of the search results are identified and applications that are relevant to the characteristics are determined. The determination of relevant applications include: accessing an application manifest that manages a mapping between applications and predefined characteristics; comparing the characteristics of the search results against the predefined characteristics of the application manifest to determine a match; and, when a match exists between the search-result characteristics and the predefined characteristics, identifying applications mapped to the matched characteristics as being relevant to the search results. These identified applications are presented in response to the query.

Integrating applications within search results

Systems, methods, and computer media for identifying query rewriting replacement terms are provided. A list of related string pairs each comprising a first string and second string is received. The first string of each related string pair is a user search query extracted from user click log data. For one or more of the related string pairs, the string pair is provided as inputs to a statistical machine translation model. The model identifies one or more pairs of corresponding terms, each pair of corresponding terms including a first term from the first string and a second term from the second string. The model also calculates a probability of relatedness for each of the one or more pairs of corresponding terms. Term pairs whose calculated probability of relatedness exceeds a threshold are characterized as query term replacements and incorporated, along with the probability of relatedness, into a query rewriting candidate database.

Enhanced query rewriting through statistical machine translation

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Bellevue, WA, United States of America

Sanaz Ahari