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DEXA
2005
Springer

Improved Sequential Pattern Mining Using an Extended Bitmap Representation

10 years 8 months ago
Improved Sequential Pattern Mining Using an Extended Bitmap Representation
The main challenge of mining sequential patterns is the high processing cost of support counting for large amount of candidate patterns. For solving this problem, SPAM algorithm was proposed in SIGKDD’2002, which utilized a depth-first traversal on the search space combined with a vertical bitmap representation to provide efficient support counting. According to its experimental results, SPAM outperformed the previous works SPADE and PrefixSpan algorithms on large datasets. However, the SPAM algorithm is efficient under the assumption that a huge amount of main memory is available such that its practicability is in question. In this paper, an Improved-version of SPAM algorithm, called I-SPAM, is proposed. By extending the structures of data representation, several heuristic mechanisms are proposed to speed up the efficiency of support counting further. Moreover, the required memory size for storing temporal data during mining process of our method is less than the one needed by SPAM....
Chien-Liang Wu, Jia-Ling Koh, Pao-Ying An
Added 26 Jun 2010
Updated 26 Jun 2010
Type Conference
Year 2005
Where DEXA
Authors Chien-Liang Wu, Jia-Ling Koh, Pao-Ying An
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