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首页> 外文会议>Bioinformatics and Biomedical Engineering , 2009. ICBBE 2009 >An Efficient Subsequences Mining Algorithm
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An Efficient Subsequences Mining Algorithm

机译：一种高效的子序列挖掘算法

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摘要

As a step forward to analyzing patterns in sequences, we introduce the problem of mining closed repetitive gapped subsequences and propose efficient solutions. Given a database of sequences where each sequence is an ordered list of events, the pattern we would like to mine is called repetitive gapped subsequence. Different from the sequential pattern mining problem, repetitive support captures not only repetitions of a pattern in different sequences but also the repetitions within a sequence. Given a users-specified support threshold min_sup, we study finding the set of all patterns with repetitive support no less than min_sup. To obtain a compact yet complete result set and improve the efficiency, we also study finding closed patterns. Efficient mining algorithms to find the complete set of desired patterns are proposed based on the idea of instance growth. Our performance study on various datasets shows the efficiency of our approach. A case study is also performed to show the utility of our approach.
机译：作为分析序列模式的一步，我们介绍了挖掘封闭的重复缺口子序列的问题，并提出了有效的解决方案。给定一个序列数据库，其中每个序列都是事件的有序列表，我们要挖掘的模式称为重复空缺子序列。与顺序模式挖掘问题不同，重复支持不仅捕获不同序列中模式的重复，而且捕获序列中的重复。给定用户指定的支持阈值min_sup，我们研究查找具有不小于min_sup的重复支持的所有模式的集合。为了获得紧凑而完整的结果集并提高效率，我们还研究了寻找闭合模式。基于实例增长的思想，提出了一种有效的挖掘算法，以找到所需模式的完整集合。我们对各种数据集的性能研究表明了我们方法的有效性。还进行了案例研究，以显示我们方法的实用性。

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