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Detecting anomalies in work practice data by combining multiple domains of information

机译:通过组合多个信息域来检测工作实践数据中的异常

摘要

One embodiment of the present invention provides a system for multi-domain clustering. During operation, the system collects domain data for at least two domains associated with users, wherein a domain is a source of data describing observable activities of a user. Next, the system estimates a probability distribution for a domain associated with the user. The system also estimates a probability distribution for a second domain associated with the user. Then, the system analyzes the domain data with a multi-domain probability model that includes variables for two or more domains to determine a probability distribution of each domain associated with the probability model and to assign users to clusters associated with user roles.
机译:本发明的一个实施例提供了一种用于多域集群的系统。在操作期间,系统收集与用户相关联的至少两个域的域数据,其中域是描述用户的可观察活动的数据源。接下来,系统估计与用户相关联的域的概率分布。系统还估计与用户相关联的第二域的概率分布。然后,系统使用包含两个或多个域变量的多域概率模型分析域数据,以确定与该概率模型关联的每个域的概率分布,并将用户分配给与用户角色关联的集群。

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