期刊名称：International Journal of Computer Technology and Applications
电子版ISSN：2229-6093
出版年度：2012
卷号：3
期号：3
页码：1125-1131
出版社：Technopark Publications
摘要：Sequential pattern mining is to find sequential purchasing behaviors for most customers from a large amount of customer transactions. Historical transaction data can be analyzed to discover customer purchasing habits. However, the size of the transaction database can be very large. It is very time consuming to find all the sequential patterns from a large database, and users may be only interested in some items. Sequential pattern mining based on constraint is now an important research issue of data mining, because it can reduce useless candidate generation as well as make the generated patterns meet the requirements of special users. Thus focus of this research paper is to find sequential patterns which satisfy various constraints and thus generating only interesting patterns and saving computational cost. We can push multiple constraints in sequential pattern mining to enhance the performance
