An efficient dynamic superset bit-vector approach for mining frequent closed itemsets and their lattice structure
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- 作者：Tahrima Hashema ; tahrimacsedu14@gmail.com" class="auth_mail" title="E-mail the corresponding author ; Md. Rezaul Karima ; rkarim@cse.univdhaka.edu" class="auth_mail" title="E-mail the corresponding author ; Md. Samiullaha ; samiullah@cse.univdhaka.edu" class="auth_mail" title="E-mail the corresponding author ; Chowdhury Farhan Ahmed ; a ; b ; cfahmed@unistra.fr" class="auth_mail" title="E-mail the corresponding author ; farhan@cse.univdhaka.edu" class="auth_mail" title="E-mail the corresponding author
- 关键词：Data mining ; Association rules ; Frequent closed itemset ; Frequent closed itemset lattice
- 刊名：Expert Systems with Applications
- 出版年：2017
- 出版时间：January 2017
- 年：2017
- 卷：67
- 期：Complete
- 页码：252-271
- 全文大小：2755 K
文摘
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Efficient approach to mine frequent closed itemsets and their lattice structure.
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We propose a new memory efficient dynamic superset bit-vector (DSBV) structure.
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New candidate pruning techniques are developed.
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DSBV establishes hierarchical subset-superset relationship of itemset lattice.
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Extensive experiments to show scalability and supremacy of our proposed approach.