Modifying search result ranking based on implicit user feedback

    公开(公告)号:US11188544B1

    公开(公告)日:2021-11-30

    申请号:US16299130

    申请日:2019-03-11

    Applicant: Google LLC

    Abstract: The present disclosure includes systems and techniques relating to ranking search results of a search query. In general, the subject matter described in this specification can be embodied in a computer-implemented method that includes determining a measure of relevance for a document result within a context of a search query for which the document result is returned, the determining being based on a first number in relation to a second number, the first number corresponding to longer views of the document result, and the second number corresponding to at least shorter views of the document result; and outputting the measure of relevance to a ranking engine for ranking of search results, including the document result, for a new search corresponding to the search query. The subject matter described in this specification can also be embodied in various corresponding computer program products, apparatus and systems.

    Generating context-based spell corrections of entity names

    公开(公告)号:US10162895B1

    公开(公告)日:2018-12-25

    申请号:US14616915

    申请日:2015-02-09

    Applicant: Google LLC

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for correcting entity names. One method includes receiving texts and deriving a plurality of name-context pairs from the texts. The method further includes calculating a context consistency measure for each name-context pair and storing context-entity name data representing the name-context pairs. Another method includes identifying an entity name and one or more context terms from a query and generating candidate names for the entity name. The method further includes determining a score for each of the candidate names, selecting a number of top scoring candidate names, and using the selected candidate names to respond to the query.

    Modifying search result ranking based on implicit user feedback

    公开(公告)号:US11816114B1

    公开(公告)日:2023-11-14

    申请号:US17533973

    申请日:2021-11-23

    Applicant: Google LLC

    Abstract: The present disclosure includes systems and techniques relating to ranking search results of a search query. In general, the subject matter described in this specification can be embodied in a computer-implemented method that includes determining a measure of relevance for a document result within a context of a search query for which the document result is returned, the determining being based on a first number in relation to a second number, the first number corresponding to longer views of the document result, and the second number corresponding to at least shorter views of the document result; and outputting the measure of relevance to a ranking engine for ranking of search results, including the document result, for a new search corresponding to the search query. The subject matter described in this specification can also be embodied in various corresponding computer program products, apparatus and systems.

    Locating meaningful stopwords or stop-phrases in keyword-based retrieval systems

    公开(公告)号:US10452718B1

    公开(公告)日:2019-10-22

    申请号:US15787276

    申请日:2017-10-18

    Applicant: Google LLC

    Abstract: A stopword detection component detects stopwords (also stop-phrases) in search queries input to keyword-based information retrieval systems. Potential stopwords are initially identified by comparing the terms in the search query to a list of known stopwords. Context data is then retrieved based on the search query and the identified stopwords. In one implementation, the context data includes documents retrieved from a document index. In another implementation, the context data includes categories relevant to the search query. Sets of retrieved context data are compared to one another to determine if they are substantially similar. If the sets of context data are substantially similar, this fact may be used to infer that the removal of the potential stopword(s) is not material to the search. If the sets of context data are not substantially similar, the potential stopword can be considered material to the search and should not be removed from the query.

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