Title: A flexible and efficient sequential pattern mining algorithm

Authors: Jie-Ru Lin, Chia-Ying Hsieh, Don-Lin Yang, Jungpin Wu, Ming-Chuan Hung

Addresses: Department of Information Engineering and Computer Science, Feng Chia University, 100, Wenhwa Road, Taichung, Taiwan. ' Department of Information Engineering and Computer Science, Feng Chia University, 100, Wenhwa Road, Taichung, Taiwan. ' Department of Information Engineering and Computer Science, Feng Chia University, 100, Wenhwa Road, Taichung, Taiwan. ' Department of Statistics, Feng Chia University, 100, Wenhwa Road, Taichung, Taiwan. ' Department of Industrial Engineering and Systems Management, Feng Chia University, 100, Wenhwa Road, Taichung, Taiwan

Abstract: Sequential pattern mining has gathered great attention in recent years due to its broad applications. Most of the existing methods are in two categories: 1) candidate-generation-and-test approaches such as GSP, requiring multiple database scans, 2) pattern-growth approaches such as PrefixSpan, scanning the projected database which may be several times larger than the original database. Methods from both categories must set minimum support thresholds in advance. To remedy the problems, we propose a new approach, Fast Sequential Pattern Enumeration (FSPE), to mine sequential patterns without the need to predetermine the minimum support threshold. The FSPE scans the transaction database only once to enumerate all candidate sequences with efficient indexing of their support counters. Using our approach one can easily produce meaningful rules for any item that appears at least once in the sequence database.

Keywords: data mining; sequential pattern mining; enumeration; minimum support; sequential patterns; sequence databases.

DOI: 10.1504/IJIIDS.2009.027688

International Journal of Intelligent Information and Database Systems, 2009 Vol.3 No.3, pp.291 - 310

Published online: 07 Aug 2009 *

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