Negative-GSP: an efficient method for mining negative sequential patterns

Authors:
Zhigang Zheng;Yanchang Zhao;Ziye Zuo;Longbing Cao
Affiliations:
University of Technology, Sydney, Australia;University of Technology, Sydney, Australia;University of Technology, Sydney, Australia;University of Technology, Sydney, Australia
Venue:
AusDM '09 Proceedings of the Eighth Australasian Data Mining Conference - Volume 101
Year:
2009

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Abstract

Different from traditional positive sequential pattern mining, negative sequential pattern mining considers both positive and negative relationships between items. Negative sequential pattern mining doesn't necessarily follow the Apriori principle, and the searching space is much larger than positive pattern mining. Giving definitions and some constraints of negative sequential patterns, this paper proposes a new method for mining negative sequential patterns, called Negative-GSP. Negative-GSP can find negative sequential patterns effectively and efficiently by joining and pruning, and extensive experimental results show the efficiency of the method.