Computer Engineering and Applications ›› 2013, Vol. 49 ›› Issue (23): 106-111.
Previous Articles Next Articles
YUAN Hongjuan
Online:
Published:
袁红娟
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
YUAN Hongjuan. GFExtractor:algorithm of mining non-redundant episode rules effectively in event sequence[J]. Computer Engineering and Applications, 2013, 49(23): 106-111.
袁红娟. GFExtractor:事件序列上有效挖掘无冗余情节规则的算法[J]. 计算机工程与应用, 2013, 49(23): 106-111.
0 / Recommend
Add to citation manager EndNote|Ris|BibTeX
URL: http://cea.ceaj.org/EN/
http://cea.ceaj.org/EN/Y2013/V49/I23/106