An efficient dynamic superset bit-vector approach for mining frequent closed itemsets and their lattice structure
作者：
Highlights：
• Efficient approach to mine frequent closed itemsets and their lattice structure.
• We propose a new memory efficient dynamic superset bit-vector (DSBV) structure.
• New candidate pruning techniques are developed.
• DSBV establishes hierarchical subset-superset relationship of itemset lattice.
• Extensive experiments to show scalability and supremacy of our proposed approach.
摘要
•Efficient approach to mine frequent closed itemsets and their lattice structure.•We propose a new memory efficient dynamic superset bit-vector (DSBV) structure.•New candidate pruning techniques are developed.•DSBV establishes hierarchical subset-superset relationship of itemset lattice.•Extensive experiments to show scalability and supremacy of our proposed approach.
论文关键词：Data mining,Association rules,Frequent closed itemset,Frequent closed itemset lattice
论文评审过程：Received 10 May 2016, Revised 11 July 2016, Accepted 13 September 2016, Available online 22 September 2016, Version of Record 5 October 2016.
论文官网地址：https://doi.org/10.1016/j.eswa.2016.09.023
