Computer Engineering and Applications ›› 2013, Vol. 49 ›› Issue (23): 106-111.

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GFExtractor:algorithm of mining non-redundant episode rules effectively in event sequence

YUAN Hongjuan   

  1. School of Mathematics and Information, Taizhou University, Taizhou, Jiangsu 225300, China
  • Online:2013-12-01 Published:2016-06-12

GFExtractor:事件序列上有效挖掘无冗余情节规则的算法

袁红娟   

  1. 泰州学院 数理信息学院,江苏 泰州 225300

Abstract: Mining episode rules in event sequence aims to discover the causal relationship between the episodes. To mine non-redundant episode rules in event sequence, the algorithm of GFExtractor is proposed in this paper, based on the support definition of non-overlapping minimal occurrences and the depth-first search strategy. GFExtractor uses the pruning technology to eliminate non-generator episodes, and uses the forward and backward extension check to eliminate non-closed episodes.  Non-redundant episode rules are generated between a superset of Gen and FCE. Experimental results confirm the validity of algorithm in mining non-redundant episode rules in event sequence.

Key words: episode generator, frequent closed episode, episode rules

摘要: 事件序列上挖掘情节规则,旨在发现情节之间的因果关系。基于非重叠的最小发生的支持度定义及深度优先搜索策略,提出在事件序列上挖掘无冗余情节规则的GFExtractor算法。利用非生成子情节的剪枝策略,淘汰非生成子情节;利用向前、向后扩展检查,淘汰非闭情节;最终在情节生成子集Gen与频繁闭情节集FCE之间产生无冗余的情节规则。实验结果证实了算法在事件序列上挖掘无冗余情节规则的有效性。

关键词: 情节生成子, 频繁闭情节, 情节规则