发明申请
US20120191640A1 MINING TEMPORAL PATTERNS IN LONGITUDINAL EVENT DATA USING DISCRETE EVENT MATRICES AND SPARSE CODING
有权
使用离散事件矩阵和稀疏编码的长期事件数据挖掘时间模式
- 专利标题: MINING TEMPORAL PATTERNS IN LONGITUDINAL EVENT DATA USING DISCRETE EVENT MATRICES AND SPARSE CODING
- 专利标题(中): 使用离散事件矩阵和稀疏编码的长期事件数据挖掘时间模式
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申请号: US13011632申请日: 2011-01-21
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公开(公告)号: US20120191640A1公开(公告)日: 2012-07-26
- 发明人: Shahram Ebadollahi , Jiaying Hu , Martin S. Kohn , Noah Lee , Robert K. Sorrentino , Jimeng Sun , Fei Wang
- 申请人: Shahram Ebadollahi , Jiaying Hu , Martin S. Kohn , Noah Lee , Robert K. Sorrentino , Jimeng Sun , Fei Wang
- 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
- 主分类号: G06N5/02
- IPC分类号: G06N5/02
摘要:
Methods and systems for event pattern mining are shown that include representing longitudinal event data in a measurable geometric space as a temporal event matrix representation (TEMR) using spatial temporal shapes, wherein event data is organized into hierarchical categories of event type and performing temporal event pattern mining with a processor by locating visual event patterns among the spatial temporal shapes of said TEMR using a constraint sparse coding framework.
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