期刊名称：International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN：2277-6451
电子版ISSN：2277-128X
出版年度：2013
卷号：3
期号：3
出版社：S.S. Mishra
摘要：Tremendous amount of data being collected is increasing speedily by computerized applications around the world. Hidden in the va st data, the valuable information is attracting researchers of multiple disciplines to study effective approaches to derive useful knowledge from within. Among various data mining objectives, the mining of frequent patterns has been the focus of knowledge discovery in databases. This paper aims to investigate efficient algorithm for mining sequential patterns. Mining sequential patterns with time constraints, such as time gaps and sliding time-window, may reinforce the accuracy of mining results. However, the capabilities to mine the time-constrained patterns were previously available only within Apriori framework. Recent studies indicate that pattern -growth methodology could speed up sequence mining. Current algorithms use a generate-candidate-and-test approach that may generate a large amount of candidates for dense datasets. Many candidates do not appear in the database. Therefore we are introducing a more efficient algorithm for sequential pattern mining. The time & space consumption of proposed algorithm will be lesser in comparison to previous algorithm
