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    • 4. 发明申请
    • UNIFIED AUCTION MODEL FOR SUGGESTING RECOMMENDATION UNITS AND AD UNITS
    • 推荐建议单位和AD单位的统一拍卖模式
    • US20140019233A1
    • 2014-01-16
    • US13549080
    • 2012-07-13
    • Andrey GoderDavid YeYanxin ShiJohn Hegeman
    • Andrey GoderDavid YeYanxin ShiJohn Hegeman
    • G06Q30/02
    • A social networking system presents advertisements and recommendation units to its users. The recommendation units suggest actions for the users to increase their engagement with the social networking system or otherwise interact with other users, while the social networking system receives revenue from advertisers for displaying advertisements based on bid values associated with the advertisements. The social networking system determines values for the advertisements and for the recommendation units, where the values are measured in a comparable fashion. This allows the system to rank and select the advertisements and recommendation units together in a unified auction model. For example, the social networking system uses a pacing value to determine values of recommendation units having a common unit of measurement with expected values of advertisements to the social networking system.
    • 社交网络系统向用户展示广告和推荐单位。 推荐单元建议用户增加他们与社交网络系统的参与或者与其他用户交互的动作,而社交网络系统根据与广告相关联的出价值从广告商收到用于显示广告的收入。 社交网络系统确定广告和推荐单位的价值,其中值以可比较的方式测量。 这允许系统在统一的拍卖模型中对广告和推荐单元进行排名和选择。 例如,社交网络系统使用起搏值来确定具有与社交网络系统的广告的预期值的具有公共测量单位的推荐单元的值。
    • 7. 发明申请
    • Real-Time Online-Learning Object Recommendation Engine
    • 实时在线学习对象推荐引擎
    • US20130151539A1
    • 2013-06-13
    • US13313984
    • 2011-12-07
    • Yanxin ShiAndrey GoderDavid Ye
    • Yanxin ShiAndrey GoderDavid Ye
    • G06F17/30
    • G06F17/30867
    • In one embodiment, a system includes one or more computing systems that implement a social networking environment containing a large number of heterogeneous objects type, each of the plurality of object types having varying features, the system implementing a generic object recommendation engine for scoring objects and recommending the objects to users of the social networking system. In particular embodiments, the user and content object features are fed as inputs into a heuristic model that generates an expected value for the content object and user. In particular embodiments, the object recommendation engine includes an online learner that may log a user's actions after the initial impression to determine the relatively degree of interest to the user.
    • 在一个实施例中,系统包括实现包含大量异构对象类型的社交网络环境的一个或多个计算系统,所述多个对象类型中的每一个具有不同的特征,所述系统实现用于评分对象的通用对象推荐引擎, 向社交网络系统的用户推荐对象。 在特定实施例中,用户和内容对象特征作为输入被馈送到产生内容对象和用户的期望值的启发式模型中。 在特定实施例中,对象推荐引擎包括在线学习者,其可以在初始印象之后记录用户的动作以确定对用户的相对程度的兴趣。
    • 9. 发明申请
    • SUGGESTING DEALS TO A USER IN A SOCIAL NETWORKING SYSTEM
    • 在社交网络系统中为用户建议购物
    • US20120239486A1
    • 2012-09-20
    • US13181291
    • 2011-07-12
    • Bo HuYanxin Shi
    • Bo HuYanxin Shi
    • G06Q30/00
    • G06Q30/0269G06Q30/0207G06Q30/0241G06Q50/01
    • A social networking system suggests deals relevant to a user. The deals are selected for suggestion based on social information associated with the user. Social information used for selecting candidate deals for a user includes information describing other users connected to the user and their associations with the candidate deals or with related deals, for example, deals from the same provider. Associations of connections of the user with the candidate deals may be determined based on actions associated with the candidate deals performed by the connections. The actions performed by the connections may be weighted based on types of the actions to determine a measure of relevance of the candidate deal for the user. Candidate deals are selected from a set of deals by applying deal targeting criteria received from deal providers. The deal targeting criteria specify attributes describing users to be targeted for a particular deal.
    • 社交网络系统建议与用户有关的交易。 根据与用户相关联的社交信息,选择交易用于建议。 用于为用户选择候选交易的社交信息包括描述连接到用户的其他用户及其与候选交易或相关交易(例如来自相同提供商的交易)的关联的信息。 可以基于与连接执行的候选交易相关联的动作来确定用户与候选交易的连接的关联。 可以基于用于确定用户的候选交易的相关性的度量的动作的类型来对连接执行的动作进行加权。 通过从交易提供商处收到的交易定位标准,从一组交易中选出候选交易。 交易定位标准指定描述特定交易定位的用户的属性。