Analyzing user reviews to determine entity attributes

    公开(公告)号:US10061767B1

    公开(公告)日:2018-08-28

    申请号:US15625711

    申请日:2017-06-16

    Applicant: Google Inc.

    CPC classification number: G06F17/278 G06F17/2785

    Abstract: Methods and apparatus are described herein for classifying user reviews or portions thereof as being related to various entities, and for associating extracted descriptive segments of text contained in those user reviews or portions thereof with entities based on the classifications. In various implementations, one or more categories of observed user interest may be identified based on a corpus of user queries. One or more segments of text related to the one or more categories of observed user interest may be detected in one or more user reviews associated with a product. Based on the detecting, the product may be indexed on the one or more categories of observed user interest in a searchable database. In some implementations, the searchable database may be accessible to one or more remote client devices, and may be searchable by the one or more categories of observed user interest to provide search results to be rendered by the one or more remote client devices.

    Analyzing user reviews to determine entity attributes

    公开(公告)号:US09710456B1

    公开(公告)日:2017-07-18

    申请号:US14709455

    申请日:2015-05-11

    Applicant: Google Inc.

    CPC classification number: G06F17/278 G06F17/2785

    Abstract: Methods and apparatus are described herein for classifying user reviews or portions thereof as being related to various entities, and for associating extracted descriptive segments of text contained in those user reviews or portions thereof with entities based on the classifications. In various implementations, one or more portions of a corpus of user reviews may be classified as being related to a first entity or a second entity. One or more descriptive segments of text may be extracted from the one or more classified portions. The one or more extracted descriptive segments of text may be associated with the first or second entity based on classifications of the one or more classified portions.

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