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Ming-Yen Lin, Sue-Chen Hsueh+ and Chia-Wen Chang
Department of Information Engineering and Computer Science
Feng Chia University
Taichung, 407 Taiwan
+Department of Information Management
Chaoyang University of Technology
Taichung, 413 Taiwan
The mining of closed sequential patterns has attracted researchers for its capability
of using compact results to preserving the same expressive power as traditional mining.
Many studies have shown that constraints are essential for applications of sequential
patterns. However, time constraints have not been incorporated into closed sequence
mining yet. Therefore, we propose an algorithm called CTSP for closed sequential pattern
mining with time constraints. CTSP loads the database into memory and constructs
time-indexes to facilitate both pattern mining and closure checking, within the patterngrowth
framework. The index sets are utilized to efficiently mine the patterns without
generating any candidate or sub-database. The bidirectional closure checking strategy
further speeds up the mining. The comprehensive experiments with both synthetic and
real datasets show that CTSP efficiently mines closed sequential patterns satisfying the
time constraints, and has good linear scalability with respect to the database size.
Received February 2, 2007; accepted July 13, 2007.
Communicated by K. Robert Lai, Yu-Chee Tseng and Shu-Yuan Chen.
*This paper was supported by the National Science Council of Taiwan, R.O.C. under research grant No.
NSC 95-2221-E-035-114.