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....

• Type: Conference
• Year: 2005
• Where: DEXA
• Authors: Chien-Liang Wu, Jia-Ling Koh, Pao-Ying An
• Keywords: DEXA 2005, Efficient Support Counting, SPAM Algorithm, Support Counting