An Efficient Algorithm for Mining Frequent Sequential Patterns and Emerging Patterns with Various Constraints
C K Bhensdadia1, Y P Kosta2 

1C K Bhensdadia, Department of Computer Engineering, Dharmsinh Desai Institute of Technology (Faculty of Technology), Dharmsinh Desai University, Nadiad, India.
2Y P Kosta, Marwadi Education Foundation’s Group of Institutions, Rajkot, India.
Manuscript received on November 21, 2011. | Revised Manuscript received on November 30, 2011. | Manuscript published on January 05, 2012. | PP: 59-65 | Volume-1 Issue-6, January 2012. | Retrieval Number: F026811151/2012©BEIESP
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Abstract: In many cases, sequential pattern mining still faces tough challenges in both effectiveness and efficiency. On the one hand, there could be a large number of sequential patterns in a large database. A user is often interested in only a small subset of such patterns. Presenting the complete set of sequential patterns may make the mining result hard to understand and hard to use. On the other hand, although efficient algorithms have been proposed, mining a large amount of sequential patterns from large data sequence databases is very expensive task. If we can focus on only those sequential patterns interesting to users, we may be able to save a lot of computation cost by those uninteresting patterns.
Keywords: Sequential Pattern, Constraints.