Mining closed and multi-supports-based sequential pattern in high-dimensional dataset
Joint Authors
Han, Meng
Wang, Zhihai
Yuan, Jidong
Source
The International Arab Journal of Information Technology
Issue
Vol. 12, Issue 4 (31 Jul. 2015)11 p.
Publisher
Publication Date
2015-07-31
Country of Publication
Jordan
No. of Pages
11
Main Subjects
Topics
Abstract EN
Previous mining algorithms on high dimensional datasets, such as biological dataset, create very large patterns sets as a result which includes small and discontinuous sequential patterns.
These patterns do not bear any useful information for usage.
Mining sequential patterns in such sequences need to consider different forms of patterns, such as contiguous patterns, local patterns which appear more than one time in a special sequence and so on.
Mining closed pattern leads to a more compact result set but also a better efficiency.
In this paper, a novel algorithm based on BI - directional extension and multisupports is provided specifically for mining contiguous closed patterns in high dimensional dataset.
Three kinds of contiguous closed sequential patterns are mined which are sequential patterns, local sequential patterns and total sequential patterns.
Thorough performances on biological sequences have demonstrated that the proposed algorithm reduces memory consumption and generates compact patterns.
A detailed analysis of the multi-supports-based results is provided in this paper.
American Psychological Association (APA)
Han, Meng& Wang, Zhihai& Yuan, Jidong. 2015. Mining closed and multi-supports-based sequential pattern in high-dimensional dataset. The International Arab Journal of Information Technology،Vol. 12, no. 4.
https://search.emarefa.net/detail/BIM-431238
Modern Language Association (MLA)
Han, Meng…[et al.]. Mining closed and multi-supports-based sequential pattern in high-dimensional dataset. The International Arab Journal of Information Technology Vol. 12, no. 4 (Jul. 2015).
https://search.emarefa.net/detail/BIM-431238
American Medical Association (AMA)
Han, Meng& Wang, Zhihai& Yuan, Jidong. Mining closed and multi-supports-based sequential pattern in high-dimensional dataset. The International Arab Journal of Information Technology. 2015. Vol. 12, no. 4.
https://search.emarefa.net/detail/BIM-431238
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-431238