CONTENT RELEVANCE IN A SOCIAL NETWORKING SYSTEM USING QUALITY CONTROLLED HUMAN RATERS

    公开(公告)号:US20170161276A1

    公开(公告)日:2017-06-08

    申请号:US14960172

    申请日:2015-12-04

    Applicant: Facebook, Inc.

    CPC classification number: G06F17/30867 G06F17/3053 G06Q50/01

    Abstract: A social networking system builds a quality controlled and desired population-representative pool of human raters to provide ratings on content items to improve a feed ranking model used for providing its users with more relevant content. The system identifies a pool of candidate human raters for providing ratings on a feed of content items. For each candidate human rater of the pool of candidate human raters, the system presents a feed of content items based on a feed ranking model, obtains ratings on the feed of content items, and determines a score representing the consistency of the obtained ratings, the representativeness of the pool of human raters, or the relevance of the content provided by the ranking model. The system uses the computed scores to modify the ranking model used to present content to its users for improving the relevance of the presented content.

    Content relevance in a social networking system using population-representative human rater pool

    公开(公告)号:US10540627B2

    公开(公告)日:2020-01-21

    申请号:US14960179

    申请日:2015-12-04

    Applicant: Facebook, Inc.

    Abstract: A social networking system builds a quality controlled and desired population-representative pool of human raters to provide ratings on content items to improve a feed ranking model used for providing its users with more relevant content. The system identifies a pool of candidate human raters for providing ratings on a feed of content items. For each candidate human rater of the pool of candidate human raters, the system presents a feed of content items based on a feed ranking model, obtains ratings on the feed of content items, and determines a score representing the consistency of the obtained ratings, the representativeness of the pool of human raters, or the relevance of the content provided by the ranking model. The system uses the computed scores to modify the ranking model used to present content to its users for improving the relevance of the presented content.

    Content relevance in a social networking system using quality controlled human raters

    公开(公告)号:US10120945B2

    公开(公告)日:2018-11-06

    申请号:US14960172

    申请日:2015-12-04

    Applicant: Facebook, Inc.

    Abstract: A social networking system builds a quality controlled and desired population-representative pool of human raters to provide ratings on content items to improve a feed ranking model used for providing its users with more relevant content. The system identifies a pool of candidate human raters for providing ratings on a feed of content items. For each candidate human rater of the pool of candidate human raters, the system presents a feed of content items based on a feed ranking model, obtains ratings on the feed of content items, and determines a score representing the consistency of the obtained ratings, the representativeness of the pool of human raters, or the relevance of the content provided by the ranking model. The system uses the computed scores to modify the ranking model used to present content to its users for improving the relevance of the presented content.

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