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Applied Computational Intelligence and Soft Computing
Volume 2012 (2012), Article ID 593147, 7 pages
http://dx.doi.org/10.1155/2012/593147
Research Article

An Application of Improved Gap-BIDE Algorithm for Discovering Access Patterns

1Database and Bioinformatics Laboratory, Chungbuk National University, Cheongju 361-763, Republic of Korea
2Division of Science and Technology, BNU-HKBU United International College, Zhuhai 519-085, China
3Multimedia Systems Laboratory, School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu, Fukushima 965-8580, Japan

Received 9 March 2012; Revised 14 May 2012; Accepted 20 May 2012

Academic Editor: Qiangfu Zhao

Copyright © 2012 Xiuming Yu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Discovering access patterns from web log data is a typical sequential pattern mining application, and a lot of access pattern mining algorithms have been proposed. In this paper, we propose an improved approach of Gap-BIDE algorithm to extract user access patterns from web log data. Compared with the previous Gap-BIDE algorithm, a process of getting a large event set is proposed in the provided algorithm; the proposed approach can find out the frequent events by discarding the infrequent events which do not occur continuously in an accessing time before generating candidate patterns. In the experiment, we compare the previous access pattern mining algorithm with the proposed one, which shows that our approach is very efficient in discovering access patterns in large database.