发明授权
- 专利标题： Recovering the structure of sparse markov networks from high-dimensional data
- 专利标题（中）： 从高维数据恢复稀疏马尔科夫网络的结构
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申请号： US12551297申请日： 2009-08-31
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公开(公告)号： US08326787B2公开(公告)日： 2012-12-04
- 发明人: Narges Bani Asadi , Guillermo A. Cecchi , Dimitri Kanevsky , Bhuvana Ramabhadran , Irina Rish , Katya Scheinberg
- 申请人： Narges Bani Asadi , Guillermo A. Cecchi , Dimitri Kanevsky , Bhuvana Ramabhadran , Irina Rish , Katya Scheinberg
- 申请人地址： US NY Armonk
- 专利权人： International Business Machines Corporation
- 当前专利权人： International Business Machines Corporation
- 当前专利权人地址： US NY Armonk
- 代理机构： Fleit Gibbons Gutman Bongini & Bianco PL
- 代理商 Jose Gutman
- 主分类号： G06F17/00
- IPC分类号： G06F17/00 ; G06F7/60 ; G06F3/00
摘要：
A method, information processing system, and computer readable article of manufacture model data. A first dataset is received that includes a first set of physical world data. At least one data model associated with the first dataset is generated based on the receiving. A second dataset is received that includes a second set of physical world data. The second dataset is compared to the at least one data model. A probability that the second dataset is modeled by the at least one data model is determined. A determination is made that the probability is above a given threshold. A decision associated with the second dataset based on the at least one data model is generated in response to the probability being above the given threshold. The probability and the decision are stored in memory. The probability and the decision are provided to user via a user interface.
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