METHODS, SYSTEMS AND TECHNIQUES FOR RANKING BLENDED CONTENT RETRIEVED FROM MULTIPLE DISPARATE CONTENT SOURCES

    公开(公告)号:US20190332605A1

    公开(公告)日:2019-10-31

    申请号:US16510042

    申请日:2019-07-12

    Applicant: Oath Inc.

    Abstract: The present teaching, which includes methods, systems and computer-readable media, relates to ranking content from multiple disparate sources including a person's personal data sources and non-personal data sources. The disclosed techniques may include obtaining a plurality sets of content associated with a request from a person, each of which being from a separate data source, and applying a model for each set of content to obtain a set of features for each piece of content in the set of content, wherein the model is specific to a data source from where the set of content comes from. Each set of features for each piece of content of the set of content may be normalized with respect to a common space to generate a normalized feature set. Further, a score for each piece of content from a set of content may be estimated based on the normalized feature set for the piece of content, and based on the score of the piece of content, each piece of content of the plurality sets of content may be ranked.

    Content recommendation
    6.
    发明授权

    公开(公告)号:US10740415B2

    公开(公告)日:2020-08-11

    申请号:US14930218

    申请日:2015-11-02

    Applicant: Oath Inc.

    Abstract: Briefly, embodiments of methods and/or systems for performing content recommendation are disclosed. For one embodiment, as an example, estimating relevance may include computing an inner product of latent factors corresponding to a plurality of users and features of one or more content items.

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