An efficient dynamic switching algorithm for mining colossal closed itemsets from high dimensional datasets
作者：
Highlights：
• An efficient Rowset Cardinality Table based closeness checking method was proposed.
• An efficient Rowset Cardinality Table based pruning strategy was proposed.
• Proposed Algorithm dynamically switches between row and feature enumeration method.
• An efficient Itemset Support Table (IST) based closeness checking method was proposed.
• An efficient Itemset Support Table (IST) based pruning strategy was proposed.
摘要
•An efficient Rowset Cardinality Table based closeness checking method was proposed.•An efficient Rowset Cardinality Table based pruning strategy was proposed.•Proposed Algorithm dynamically switches between row and feature enumeration method.•An efficient Itemset Support Table (IST) based closeness checking method was proposed.•An efficient Itemset Support Table (IST) based pruning strategy was proposed.
论文关键词：Bioinformatics,High dimensional dataset,Preprocessing,Frequent Colossal Closed Itemsets,Rowset,Closeness,Pruning strategy
论文评审过程：Received 7 March 2018, Revised 24 May 2019, Accepted 22 July 2019, Available online 24 July 2019, Version of Record 8 November 2019.
论文官网地址：https://doi.org/10.1016/j.datak.2019.101721
