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Performance Evaluation of Sequential Pattern Mining Algorithms

Publication Type : Journal Article

Publisher : International Journal of Applied Engineering Research

Source : International Journal of Applied Engineering Research, Research India Publications, Volume 10, Issue 55, p.1918-1921 (2015)

Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-84942847657&partnerID=40&md5=94525f2456ee7078163276050e06169f

Campus : Coimbatore

School : School of Engineering

Department : Computer Science

Year : 2015

Abstract : The Sequential Pattern Mining is an extraction of relevant patterns, satisfying the minimum support threshold, where the values are delivered in a sequence and the count of the data-sequences that contain the patternis called the support of the pattern. The major goal of sequential pattern mining is to discover a complete set of possible sequential patterns from a large dataset, with small number of database scans which is used to make some business developments. This paper investigates three sequential pattern mining algorithms viz. Apriori based approach, PatternGrowthapproach and Constraint based approach for mining sequential patterns based on the number of patterns generated and running time of the algorithm. The dataset used for the experiments to mine sequential pattern is the Restaurant Database System. © Research India Publications.

Cite this Research Publication : R. Dhivyapriya, Monisha, N., and Subathra P., “Performance Evaluation of Sequential Pattern Mining Algorithms”, International Journal of Applied Engineering Research, vol. 10, no. 55, pp. 1918-1921, 2015.

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