Fast mining maximal sequential patterns

Authors:
Nancy P. Lin;Wei-Hua Hao;Hung-Jen Chen;Hao-En Chueh;Chung-I Chang
Affiliations:
Department of Computer Science and Information Engineering, Tamkang University, Taipei, Taiwan, R.O.C.;Department of Computer Science and Information Engineering, Tamkang University, Taipei, Taiwan, R.O.C.;Department of Computer Science and Information Engineering, Tamkang University, Taipei, Taiwan, R.O.C. and Department of Industrial Engineering and Management, St. John's University, Taipei, Taiwa ...;Department of Computer Science and Information Engineering, Tamkang University, Taipei, Taiwan, R.O.C.;Department of Computer Science and Information Engineering, Tamkang University, Taipei, Taiwan, R.O.C.
Venue:
SMO'07 Proceedings of the 7th WSEAS International Conference on Simulation, Modelling and Optimization
Year:
2007

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Abstract

Sequential patterns mining is now widely used in many areas, such as the analysis of e-Learning sequential patterns, web log analysis, customer buying behavior analysis and etc. In the discipline of data mining, runtime and search space are always the two major issues. In this paper, we had study many previous works to analyze these two problems, and propose a new algorithm with more condense structure and faster process to find out the complete frequent sequential patterns.