A weighted N-list-based method for mining frequent weighted itemsets

作者：

Highlights：

• Weighted N-list structure is developed.

• Theorems 3, 4 and 6 are proposed to fast calculate the weighted support of itemsets.

• Theorem 5 is proposed reduce the time complexity.

• NFWI algorithm is built based on these theorems for efficiently mining frequent weighted itemsets.

• The proposed method is efficient than the existing methods, especially when run on very large databases.

摘要

•Weighted N-list structure is developed.•Theorems 3, 4 and 6 are proposed to fast calculate the weighted support of itemsets.•Theorem 5 is proposed reduce the time complexity.•NFWI algorithm is built based on these theorems for efficiently mining frequent weighted itemsets.•The proposed method is efficient than the existing methods, especially when run on very large databases.

论文关键词：Data mining,Frequent weighted itemsets,Weighted N-list,Weighted support

论文评审过程：Received 4 July 2017, Revised 13 October 2017, Accepted 15 October 2017, Available online 16 October 2017, Version of Record 5 January 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.10.039