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PrefixSpan Algorithm for Finding Sequential Pattern with Various Constraints

Pratik Saraf, R. R Sedamkar, Sheetal Rathi Published in Artificial Intelligence

International Journal of Applied Information Systems
Year of Publication: 2015
© 2015 by IJAIS Journal
10.5120/ijais15-451380
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  1. Pratik Saraf, R R Sedamkar and Sheetal Rathi. Article: PrefixSpan Algorithm for Finding Sequential Pattern with Various Constraints. International Journal of Applied Information Systems 9(3):37-41, June 2015. BibTeX

    @article{key:article,
    	author = "Pratik Saraf and R. R Sedamkar and Sheetal Rathi",
    	title = "Article: PrefixSpan Algorithm for Finding Sequential Pattern with Various Constraints",
    	journal = "International Journal of Applied Information Systems",
    	year = 2015,
    	volume = 9,
    	number = 3,
    	pages = "37-41",
    	month = "June",
    	note = "Published by Foundation of Computer Science, New York, USA"
    }
    

Abstract

PrefixSpan (Prefix-projected Sequential pattern mining) algorithm is very well known algorithm for sequential data mining. It extracts the sequential patterns through pattern growth method. The algorithm performs very well for small datasets. As the size of datasets increases the overall time for finding the sequential patterns also get increased. The PrefixSpan algorithm is run on different datasets and results are drawn based on minimum support value. One new parameter maximum prefix length is also considered while running the algorithm. Through maximum prefix length parameter the length of prefix pattern is set which is helpful for running the algorithm on large datasets. The paper also shows the variation in time complexity and memory utilization while running the algorithm on different size of input sequential datasets.

Reference

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Keywords

PrefixSpan Algorithm, Minimum support, Maximum prefix length, Time complexity, Memory utilization.