SYSTEMS AND METHODS FOR PREDICTING PAGE ACTIVITY TO OPTIMIZE PAGE RECOMMENDATIONS

    公开(公告)号:US20170186101A1

    公开(公告)日:2017-06-29

    申请号:US14981029

    申请日:2015-12-28

    Applicant: Facebook, Inc.

    Abstract: Systems, methods, and non-transitory computer-readable media can determine a plurality of candidate entities for recommendation to a user of a social networking system. A predicted activity objective value model configured to calculate activity stores for candidate entities is established. The activity score is indicative of the probability of future activity on the social networking system by a candidate entity. A first activity score is determined for each of the plurality of candidate entities based on the predicted activity object value model and a first set of feature values. A second activity score is determined for each of the plurality of candidate entities based on the predicted activity object value model and a second set of feature values that is different from the first set of feature values. A first entity is selected of the plurality of candidate entities based on the first and second activity scores.

    Ranking and Filtering Groups Recommendations
    14.
    发明申请
    Ranking and Filtering Groups Recommendations 审中-公开
    排名和过滤组建议

    公开(公告)号:US20150370798A1

    公开(公告)日:2015-12-24

    申请号:US14308536

    申请日:2014-06-18

    Applicant: Facebook, Inc.

    Abstract: In one embodiment, a set of user groups of a social-networking system may be accessed. A first subset of the user groups may be determined for a particular user of the social-networking system, based on one or more filtering criteria. A number of recommendation-source processes may be applied to the first subset to determine a number of second subsets of the first set. Each recommendation-source process may represent a particular recommendation source. The second subsets may be combined into a list of user groups. The list of user groups may be ranked, and sent to the particular user.

    Abstract translation: 在一个实施例中,可以访问社交网络系统的一组用户组。 可以基于一个或多个过滤标准来为社交网络系统的特定用户确定用户组的第一子集。 可以将许多推荐源过程应用于第一子集以确定第一集合的第二子集的数量。 每个推荐来源过程可能代表特定的推荐来源。 第二个子集可以组合成用户组列表。 可以对用户组的列表进行排名,并将其发送给特定用户。

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