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Combination of dynamic bit vectors and transaction information for mining frequent closed sequences efficiently

机译:动态位向量和交易信息的组合,可有效地挖掘频繁的封闭序列

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摘要

Sequence mining algorithms attempt to mine all possible frequent sequences. These algorithms produce redundant results, increasing the required storage space and runtime, especially for large sequence databases. In recent years, many studies have proved that mining frequent closed sequences is more efficient than mining all frequent sequences. The desired information can be fully extracted from frequent closed sequences. Most algorithms for mining frequent closed sequences use a candidate maintenance-and-test paradigm. The present paper proposes an algorithm called CloFS-DBV that uses dynamic bit vectors. Various methods are employed to reduce memory usage and runtime. Experimental results show that CloFS-DBV is more efficient than the BIDE and CloSpan algorithms in terms of execution time and memory usage.
机译:序列挖掘算法尝试挖掘所有可能的频繁序列。这些算法产生冗余结果,从而增加了所需的存储空间和运行时间,尤其是对于大型序列数据库。近年来,许多研究证明挖掘频繁的闭合序列比挖掘所有频繁的序列更有效。可以从频繁的封闭序列中完全提取所需的信息。大多数用于挖掘频繁闭合序列的算法都使用候选的维护测试范式。本文提出了一种使用动态位向量的称为CloFS-DBV的算法。采用了各种方法来减少内存使用量和运行时间。实验结果表明,CloFS-DBV在执行时间和内存使用方面比BIDE和CloSpan算法更有效。

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