| 基于广义后缀树的事件序列频繁情节挖掘算法 |
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| 引用本文： | 曲文龙,杨炳儒,张克君.基于广义后缀树的事件序列频繁情节挖掘算法[J].北京科技大学学报,2006,28(5):490-496. |
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| 作者姓名： | 曲文龙 杨炳儒 张克君 |
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| 作者单位： | 1. 石家庄经济学院,石家庄,050031;北京科技大学信息工程学院,北京,100083
2. 北京科技大学信息工程学院,北京,100083 |
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| 摘 要： | 为了有效地挖掘事件序列频繁情节,提出了一种广义后缀树结构发现和存储频繁情节. 此结构利用广义后缀概念并且树中只包含频繁情节结点,用频繁情节发生列表逐层构建的方法提高了建树效率. 该方法充分利用了事件序列的有序特点,可用于发现各类频繁情节. 实验结果表明该算法性能优于Apriori-like频繁情节发现算法.
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| 关 键 词： | 事件序列 频繁情节 数据挖掘 广义后缀树 广义后缀树 事件序列 频繁情节 挖掘算法 generalized based event sequence frequent episodes algorithm 发现算法 算法性能 结果 实验 有序 效率 方法 发生 结点 利用 树结构 |
| 收稿时间： | 2005-03-14 |
| 修稿时间： | 2005-10-11 |
Mining algorithm of frequent episodes in an event sequence based on generalized suffix-tree |
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| QU Wenlong,YANG Bingru,ZHANG Kejun.Mining algorithm of frequent episodes in an event sequence based on generalized suffix-tree[J].Journal of University of Science and Technology Beijing,2006,28(5):490-496. |
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| Authors: | QU Wenlong YANG Bingru ZHANG Kejun |
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| Abstract: | In order to mine frequent episodes from an event sequence efficiently, an algorithm based on generalized suffix-tree was proposed to discover and store frequent episodes, which uses the concept of generalized suffix and contains only frequent episodes' nodes. The occurrence list of frequent episodes was used layer-upon-layer to improve the efficiency of the tree. The algorithm make full use of the order character of an event sequence and may discover the variety of frequent episodes. Experimental results show that the proposed algorithm is superior in runtime to Apriori-like frequent episodes mining algorithm. |
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| Keywords: | event sequence frequent episodes data mining generalized suffix tree |
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