发明申请
US20080201397A1 SEMI-AUTOMATIC SYSTEM WITH AN ITERATIVE LEARNING METHOD FOR UNCOVERING THE LEADING INDICATORS IN BUSINESS PROCESSES
有权
采用迭代学习方法的半自动系统,用于在业务流程中发现领先指标
- 专利标题: SEMI-AUTOMATIC SYSTEM WITH AN ITERATIVE LEARNING METHOD FOR UNCOVERING THE LEADING INDICATORS IN BUSINESS PROCESSES
- 专利标题(中): 采用迭代学习方法的半自动系统,用于在业务流程中发现领先指标
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申请号: US11676816申请日: 2007-02-20
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公开(公告)号: US20080201397A1公开(公告)日: 2008-08-21
- 发明人: Wei Peng , Philip C. Rose , Tong Sun
- 申请人: Wei Peng , Philip C. Rose , Tong Sun
- 主分类号: G06F17/10
- IPC分类号: G06F17/10 ; G06F17/15 ; G06F7/32 ; G06F9/44 ; G06G7/48
摘要:
Embodiments herein select performance indicators from raw data and measure the indicators over at least one time period to extract a time series of data for each of the indicators. The methods filter out redundant indicators to produce a reduced indicator set of time series of data. The embodiments detect correlations among the time series of data within the reduced indicator set by considering time-shifts between the time series of data so as to identify correlated indicators. The method determines a time order among the correlated indicators and determines a causal direction among the correlated indicators based on which of the correlated indicators occurs first in time so as to identify relative leading indicators among the correlated indicators. However, if the correlated indicators occur at approximately a same time, the determining of the causal direction is based on a relative ability of each of the indicators to predict behavior of another of the correlated indicators. The processes of determining the time order and determining the causal direction can comprise applying Dynamic Time Warping and/or Granger Causality techniques to the time series of data.
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