An algorithm for fast mining top-rank-k frequent patterns based on node-list data structure

Wang, Qian; Ren, Jiadong; N Davis, Darryl; Cheng, Yongqiang

Abstract

Frequent pattern mining usually requires much run time and memory usage. In some applications, only the patterns with top frequency rank are needed. Because of the limited pattern numbers, quality of the results is even more important than time and memory consumption. A Frequent Pattern algorithm for mining Top-rank-K patterns, FP_TopK, is proposed. It is based on a Node-list data structure extracted from FTPP-tree. Each node is with one or more triple sets, which contain supports, preorder and post-order transversal orders for candidate pattern generation and top-rank-k frequent pattern mining. FP_TopK uses the minimal support threshold for pruning strategy to guarantee that each pattern in the top-rank-k table is really frequent and this further improves the efficiency. Experiments are conducted to compare FP_TopK with iNTK and BTK on four datasets. The results show that FP_TopK achieves better performance.

Citation

Wang, Q., Ren, J., N Davis, D., & Cheng, Y. (2018). An algorithm for fast mining top-rank-k frequent patterns based on node-list data structure. Intelligent Automation and Soft Computing, 24(2), 399-404. https://doi.org/10.1080/10798587.2017.1340135

• Acceptance Date: May 20, 2017
• Online Publication Date: Sep 15, 2017
• Publication Date: 2018
• Deposit Date: Jul 11, 2017
• Publicly Available Date: Jul 11, 2017
• Journal: Intelligent automation & soft computing
• Print ISSN: 1079-8587
• Publisher: Taylor and Francis
• Peer Reviewed: Peer Reviewed
• Volume: 24
• Issue: 2
• Pages: 399-404
• DOI: https://doi.org/10.1080/10798587.2017.1340135
• Keywords: Data mining, Frequent pattern, Top-rank-k frequent pattern, FTPP-tree, Node-list
• Public URL: https://hull-repository.worktribe.com/output/453522
• Publisher URL: http://www.tandfonline.com/doi/abs/10.1080/10798587.2017.1340135?needAccess=true&journalCode=tasj20
• Additional Information: Peer Review Statement: The publishing and review policy for this title is described in its Aims & Scope.; Aim & Scope: http://www.tandfonline.com/action/journalInformation?show=aimsScope&journalCode=tasj20
• Contract Date: Jul 11, 2017