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    • 7. 发明申请
    • METHOD FOR APPROXIMATING USER TASK REPRESENTATIONS BY DOCUMENT-USAGE CLUSTERING
    • 通过文档集合对用户任务表示进行近似的方法
    • US20110125679A1
    • 2011-05-26
    • US12623717
    • 2009-11-23
    • Oliver Brdiczka
    • Oliver Brdiczka
    • G06F15/18
    • G06Q10/10G06Q10/06
    • Embodiments of the present invention provide a system for automatically creating a task representation associated with a user task. The system calculates usage footprints of a document based on other applications, documents, and people that have been accessed by the user within a predetermined time frame before and after the user accesses the document. After obtaining usage footprints of a number of documents, the system applies a clustering technique, such as spectral clustering, to create task representations, each including a collection (cluster) of documents and/or applications that are used for accomplishing a particular task. The system also filters the documents based on their average dwell times, and uses user feedback to merge or split different task clusters in order to provide accurate task representations.
    • 本发明的实施例提供了一种用于自动创建与用户任务相关联的任务表示的系统。 该系统基于在用户访问文档之前和之后的预定时间段内由用户访问的其他应用,文档和人员来计算文档的使用足迹。 在获得许多文档的使用足迹之后,系统应用诸如频谱聚类的聚类技术来创建任务表示,每个包括用于完成特定任务的文档和/或应用的集合(集群)。 系统还会根据其平均驻留时间对文档进行过滤,并使用用户反馈来合并或拆分不同的任务集群,以提供准确的任务表示。
    • 10. 发明授权
    • Identifying activities using a hybrid user-activity model
    • 使用混合用户活动模型识别活动
    • US08612463B2
    • 2013-12-17
    • US12793238
    • 2010-06-03
    • Oliver BrdiczkaShane P. AhernVictoria M. E. Bellotti
    • Oliver BrdiczkaShane P. AhernVictoria M. E. Bellotti
    • G06F17/30
    • G06Q30/02
    • In a user-activity identification technique, a user's actions are monitored while the user is using a computer. While these user actions are associated with user activities, the user activities are initially unspecified, so the tracked user actions constitute unsupervised data. Then, the tracked user actions are aggregated into subsets (for example, using clustering analysis), and user-activity classifications for the subsets (such as activity labels) are provided by the user, so the subsets constitute supervised data. Subsequently, when additional user actions (which are associated with one or more initially unspecified current user activities) are tracked, they can be associated with one or more of the classified subsets. For example, information about the additional user actions can be mapped in real time (or near real time) to one or more of the subsets using a supervised learning technique. In this way, the one or more current user activities can be identified.
    • 在用户活动识别技术中,用户在使用计算机时监视用户的动作。 虽然这些用户操作与用户活动相关联,但用户活动最初未指定,因此跟踪的用户操作构成无监督数据。 然后,跟踪的用户动作被聚合成子集(例如,使用聚类分析),并且用户为用户提供子集的用户活动分类(例如活动标签),因此子集构成监督数据。 随后,当跟踪额外的用户动作(与一个或多个最初未指定的当前用户活动相关联)时,它们可以与分类子集中的一个或多个相关联。 例如,关于附加用户动作的信息可以使用监督学习技术实时(或接近实时)映射到一个或多个子集。 以这种方式,可以识别一个或多个当前用户活动。