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DOI:
计算机系统应用英文版:2014,23(12):202-205
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事件序列上的频繁情节挖掘算法
(南京理工大学 泰州科技学院, 泰州 225300)
Algorithms for Mining Frequent Episodes on the Event Sequences
(Taizhou College of Science and Technology, NJUST, Taizhou 225300, China)
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Received:April 01, 2014    Revised:May 04, 2014
中文摘要: 事件序列上的频繁情节挖掘是时序数据挖掘领域的热点之一, 基于非重叠发生的支持度定义, 提出一个频繁情节挖掘算法NONEPI++, 该算法首先通过情节串接产生候选情节, 然后通过预剪枝和计算情节发生的时间戳来产生频繁情节. 算法只需扫描事件序列一次, 大大提高了情节挖掘的效率. 实验证明, NONEPI++算法能有效地挖掘频繁情节.
中文关键词: 事件序列  频繁情节  非重叠发生
Abstract:Mining frequent episodes on the event sequences is one of the hot areas of data mining. In this paper, support based on non-overlapped occurrence is definited. We propose an algorithm called NONEPI++ for mining frequent episodes, which firstly generate candidate episodes by join episodes, then generate frequent episodes by pre-pruning and timestamp calculating. The algorithm can improve the efficiency of mining episodes. Experiments show that NONEPI++ algorithm can effectively mine frequent episodes.
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丁勇,王云,李丛.事件序列上的频繁情节挖掘算法.计算机系统应用,2014,23(12):202-205
DING Yong,WANG Yun,LI Cong.Algorithms for Mining Frequent Episodes on the Event Sequences.COMPUTER SYSTEMS APPLICATIONS,2014,23(12):202-205