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    • 6. 发明申请
    • USING USER-ATTRIBUTE ONTOLOGIES TO CALCULATE USER-ANONYMITY DEGREES
    • 使用用户属性本地化来计算用户自主性程度
    • US20110173261A1
    • 2011-07-14
    • US12986285
    • 2011-01-07
    • DAVID P. MCCALLIE, Jr.MARGARET CUSHING KOLMCHRISTOPHER S. FINN
    • DAVID P. MCCALLIE, Jr.MARGARET CUSHING KOLMCHRISTOPHER S. FINN
    • G06F15/16
    • G06F21/6245G06F19/00G06Q50/24G16H10/60H04L63/0407H04L67/12
    • Computerized methods and systems for using user-attribute ontologies to calculate anonymity levels are provided. A semi-automated mechanism permits selective and optionally progressive exposure of demographic and clinical information to other members of a medical social network group that a member has joined. When a user decides to join a medical social network group (which may be based upon system suggestion or initiated of the user's own accord), he or she selects or creates a profile that has a statistically validated degree of anonymity, ranging from fully anonymous to fully transparent. Based upon a user's elected level of exposure, only certain data is exposed to the rest of the group's membership. Thus, the user is permitted to personally balance the tension between exposing a level of information that may render him or her personally identifiable and exposing enough information to obtain meaningful advice and/or camaraderie.
    • 提供了使用用户属性本体来计算匿名级别的计算机化方法和系统。 半自动化机制允许对成员加入的医疗社会网络组的其他成员进行人口统计学和临床​​信息的选择性和可选地逐渐暴露。 当用户决定加入医疗社交网络组(可以基于系统建议或用户自己一致发起)时,他或她选择或创建具有统计学上有效的匿名程度的简档,范围从完全匿名到 完全透明。 根据用户当选的曝光程度,只有某些数据才会暴露给该组的其他成员。 因此,允许用户亲自平衡张力,暴露可能使他或她亲自识别的信息的水平,并暴露足够的信息以获得有意义的建议和/或友情。