Google Inc.

Anwis Das

Abhinandan Sujit Das

Nitin Kumar Gupta

Renshen Wang

Nitin Gupta

Jeffrey Adgate Dean

Simon Tong

Noam M Shazeer

Othar Hansson

Michael D Levin

Emanuel Taropa

James Home

Murtaza A Basrai

Methods and apparatus for providing query suggestions to a user based on one or more past queries submitted by the user. Candidate query suggestions responsive to a current query may be identified. A candidate query similarity measure may be determined for a given candidate query suggestion based on matching entities related to the given candidate query suggestion and the one or more past queries. In some implementations, the similarity measure of the given candidate query suggestion may be based on a comparison of current entities of the given candidate query suggestion that match entities of one or more past queries, to a group of the current entities that includes entities that do not match the entities of one or more past queries. In some implementations a ranking of the candidate query suggestions may be determined based on the similarity measure.

Query suggestions based on entity collections of one or more past queries

Methods and apparatus for providing query suggestions to a user based on one or more past queries submitted by the user. Candidate query suggestions responsive to a current query may be identified. A candidate query similarity measure may be determined for a given candidate query suggestion based on matching entities related to the given candidate query suggestion and the one or more past queries. In some implementations the similarity measure may be based on cumulative entity scores of the matching entities that may optionally be based on at least one of inverse popularity of the matching entities, and how recent a past query is. In some implementations a ranking of the candidate query suggestions may be adjusted based on the similarity measure. A given candidate query suggestion may be selected as a query suggestion based on at least one of the adjusted ranking and the candidate query similarity measure.

Personalized suggestions based on past queries

Methods, systems, and apparatus, including computer program products, for generating query refinements using query components. In general, one aspect features a method that includes the acts of receiving a query comprising a plurality of terms; identifying first and second components of the query, wherein each component comprises one or more of the terms of the query and the components do not share a term from the query, and wherein the first component appears before the second component in the query; determining, for each component, a plurality of different respective component refinements; and combining the component refinements to create a plurality of query refinements for the query, including combining a first component refinement for the first component with a second component refinement for the second component to create a query refinement so that the first component refinement appears before the second component refinement in the query refinement.

Generating query refinements using query components

A computer-implemented method for identifying related search queries is performed on a server. The method includes receiving a search query from a user, identifying a set of ranked search results satisfying the search query, and identifying, using historical search query data, at least one last related search query in at least one chain of related search queries that is related to the search query and that includes at least one search result that was selected by users who issued the search query, each respective related search query in the at least one chain of related search queries except for the at least one last related search query in the at least one chain of related search queries violating a search result selection criterion. The method further includes returning the set of ranked search results and the at least one last related search query to the user.

System and method for identifying search results satisfying a search query

Methods, systems, and apparatus, including computer program products, for generating query refinements from user preference data. A group of query pairs are obtained. Each query pair includes a first query and a second query. A quality score is determined for each query pair from user preference data for documents responsive to both the first and the second query. A diversity score is determined for each query pair having a quality score satisfying a quality threshold, the diversity score determined from user preference data for documents responsive to the second, but not the first, query. For each query pair having a quality score satisfying the quality threshold and a diversity score satisfying a diversity threshold, the second query of the query pair is associated with the first query of the query pair as a candidate refinement for the first query.

Generating query refinements from user preference data

A system, computer-readable storage medium storing at least one program, and a computer-implemented method for identifying chains of related search queries is presented. Historical search query data is obtained. Chains of related search queries issued by users and search results corresponding to last related search queries in the chains of related search queries that were selected by the users are identified from the historical search query data, where each related search query in a chain of related search queries except for a last related search query in the chain of related search queries violates a search result selection criterion. The chains of related search queries are aggregated into groups, where a respective group has a common first search query and a common search result corresponding to at least one last related search query that was selected by the users. Aggregate data for the groups are stored in a query database.

Populating query suggestion database using chains of related search queries

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for reranking query completions based on activity session data. One of the methods includes receiving a query prefix from a user. Query completions are obtained for the query prefix. One or more likely queries that are likely to co-occur with a reference query in user activity sessions are obtained. If one of the likely queries matches one of the query completions, a modified ranking of the query completions is determined, including boosting a ranking of matching query completions. The modified ranking of the query completions is provided in response to receiving the query prefix.

Reranking query completions

A computer-implemented method for identifying search results satisfying a search query received from a user includes obtaining a set of ranked search results that satisfies the search query, and identifying, using historical search query data, a search result that was selected by users who issued the search query and that corresponds to at least one related search query in at least one chain of related search queries that are related to the search query. The method further includes determining, using the historical search query data, a frequency that the search query led to a selection of the identified search result; inserting the identified search result into the set of ranked search results based on the frequency that the search query led to the selection of the identified search result; and returning the set of ranked search results to the user.

Supplementing search results with historically selected search results of related queries

Methods, systems, and apparatus, including computer program products, for generating query refinements. In one implementation, a method includes dividing a search query into one or more n-grams; determining that each of the one or more n-grams represents a same concept, and in response to the determination: selecting one or more candidate refinement queries; determining one or more categories for the search query; determining one or more categories for each of the candidate refinement queries; determining a respective first score for each of the candidate refinement queries; and identifying as query refinements for the search query one or more of the candidate refinement queries based on the first scores.

Generating query refinements

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for identifying query refinements from sibling queries. In one aspect, a method includes associating each of a plurality of parent queries with a respective group of one or more child queries for the parent query, identifying one or more candidate sibling queries for a particular child query, selecting one or more final sibling queries for the particular child query from the one or more candidate sibling queries, and associating the final sibling queries with the particular child query as query refinements.

Generating sibling query refinements

A system and method is provided for providing query suggestions, particularly midstring query completions for an original query being edited or hovered over. An original query is received from a client. One or more segments in the original query are identified including an anchor segment and zero or more remaining segments. The anchor segment is identified based on cursor placement within the original query. Then one or more sibling segments associated with the anchor segment are identified. The sibling segments are identified by the server system to be semantically distinct from anchor segment. Then one or more query refinement candidates are identified. A respective query refinement candidate includes a sibling segment in place of the anchor segment and includes the remaining segments, if any, of the original query. Then information including one or more of the query refinement candidates is sent to the client for presentation.

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Sunnyvale, CA, United States of America

Anwis Das