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    • 2. 发明申请
    • METHODS AND SYSTEMS FOR MULTI-STATE RECOMMENDATIONS
    • 多国建议的方法和系统
    • WO2016054006A1
    • 2016-04-07
    • PCT/US2015/052888
    • 2015-09-29
    • THOMSON LICENSING
    • WEINSBERG, Ehud
    • G06F17/30
    • G06F17/30053
    • A recommendation system (200) can determine a first movie that has a beginning state that is close to the first state identified by the user, e.g., a sad state the user is currently in. Recommendation systems can use closeness criteria, such as determining a difference between a happiness value of the first state and a happiness value of the beginning state of the first movie, and requiring the difference to be less than a predetermined threshold value. Likewise, closeness criteria may be used to ensure the ending state of the first movie is close to the beginning state of the second movie, and to ensure the ending state of the second movie is close to the second state, e.g., the happy state desired by the user. In this way, for example, recommendation systems can provide multi-state recommendations.
    • 推荐系统(200)可以确定具有接近由用户识别的第一状态的开始状态的第一个电影,例如用户当前处于的悲观状态。推荐系统可以使用接近度标准,例如确定 所述第一状态的幸福值与所述第一影片的开始状态的幸福值之间的差异,并且要求所述差小于预定阈值。 类似地,可以使用接近度标准来确保第一电影的结束状态接近第二电影的开始状态,并且确保第二电影的结束状态接近第二状态,例如期望的快乐状态 由用户 以这种方式,例如,推荐系统可以提供多状态建议。
    • 4. 发明申请
    • METHOD AND SYSTEM FOR PRIVACY-PRESERVING RECOMMENDATIONS
    • 用于隐私保护建议的方法和系统
    • WO2015191919A1
    • 2015-12-17
    • PCT/US2015/035422
    • 2015-06-11
    • THOMSON LICENSING
    • WEINSBERG, EhudJOYE, MarcIOANNIDIS, Efstratios
    • G06F21/62G06Q30/06H04L9/00
    • G06F21/6245G06Q30/0282G06Q30/0631H04L9/008
    • Various examples of systems and methods for providing recommendations that can be tailored to a user while preserving the privacy of the user's personal information are disclosed. In various embodiments, user information can be encrypted such that the recommendation service cannot decrypt the user information, yet the recommendation service can analyze the user information to predict user ratings for content items. The predicted user ratings can remain obscured from the recommendation service by encryption, yet can provide the basis for recommendations tailored to the user. In particular, the encrypted predicted user ratings can be sent to a third party (i.e., not the recommendation service or the user), and the third party can decrypt the predicted user ratings and determine recommendations based on the predicted user ratings.
    • 公开了用于提供可以针对用户定制的建议的系统和方法的各种示例,同时保持用户的个人信息的隐私。 在各种实施例中,可以加密用户信息,使得推荐服务不能解密用户信息,但是推荐服务可以分析用户信息以预测内容项目的用户评级。 预测的用户评分可以通过加密仍然可以从推荐服务中遮蔽,但可以为用户定制的推荐提供基础。 特别地,加密的预测用户评级可以被发送到第三方(即,不是推荐服务或用户),并且第三方可以解密预测的用户评级并且基于预测的用户评级来确定推荐。
    • 6. 发明申请
    • METHOD AND SYSTEM FOR PRIVACY-PRESERVING RECOMMENDATIONS
    • 用于隐私保护建议的方法和系统
    • WO2016044129A1
    • 2016-03-24
    • PCT/US2015/049907
    • 2015-09-14
    • THOMSON LICENSING
    • JOYE, MarcWEINSBERG, EhudIOANNIDIS, Efstratios
    • H04N21/466
    • H04N21/25891H04N21/2351H04N21/251H04N21/2668H04N21/435H04N21/4668H04N21/4826
    • Various examples of systems and methods for providing recommendations that can be tailored to a user while preserving the privacy of the user's personal information are disclosed. In various embodiments, user information can be encrypted such that the recommendation service cannot decrypt the user information, yet the recommendation service can analyze the user information to predict user ratings for content items. The predicted user ratings can remain obscured from the recommendation service by encryption, yet can provide the basis for recommendations tailored to the user. In particular, encrypted comparison information of predicted user ratings can be sent to the user, and the user can decrypt the comparison and send result information to the recommender to determine recommendations.
    • 公开了用于提供可以针对用户定制的建议的系统和方法的各种示例,同时保持用户的个人信息的隐私。 在各种实施例中,可以加密用户信息,使得推荐服务不能解密用户信息,但是推荐服务可以分析用户信息以预测内容项目的用户评级。 预测的用户评分可以通过加密仍然可以从推荐服务中遮蔽,但可以为用户定制的推荐提供基础。 特别地,可以向用户发送预测用户等级的加密比较信息,并且用户可以解密比较并将结果信息发送给推荐者以确定推荐。