| 发明名称 |
DETECTING ANOMALIES IN WORK PRACTICE DATA BY COMBINING MULTIPLE DOMAINS OF INFORMATION |
| 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. |
| 申请公布号 |
US2014325643(A1) |
申请公布日期 |
2014.10.30 |
| 申请号 |
US201313871985 |
申请日期 |
2013.04.26 |
| 申请人 |
PALO ALTO RESEARCH CENTER INCORPORATED |
发明人 |
Bart Evgeniy;Liu Juan J.;Eldardiry Hoda M. A.;Price Robert R. |
| 分类号 |
H04L29/06 |
主分类号 |
H04L29/06 |
| 代理机构 |
|
代理人 |
|
| 主权项 |
1. A computer-executable method for multi-domain clustering, comprising:
collecting domain data for at least two domains associated with users, wherein a domain is a source of data describing observable activities of a user; estimating a probability distribution for a domain associated with the user; estimating a probability distribution for a second domain associated with the user; and analyzing 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. |
| 地址 |
Palo Alto CA US |
