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GTK: A Hybrid-Search Algorithm of Top-Rank-k Frequent Patterns Based on Greedy Strategy

Yuhang Long1, Wensheng Tang1, *, Bo Yang1, *, Xinyu Wang2, Hua Ma1, Hang Shi1, Xueyu Cheng3

1 Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing, Hunan Normal University, Changsha, 410081, China.
2 College of Information Science and Engineering, Hunan University, Changsha, 410082, China.
3 Clayton State University, Morrow, GA 30260, USA.

*Corresponding Authors: Wensheng Tang. Email: email; Bo Yang. Email: email.

Computers, Materials & Continua 2020, 63(3), 1445-1469.


Currently, the top-rank-k has been widely applied to mine frequent patterns with a rank not exceeding k. In the existing algorithms, although a level-wise-search could fully mine the target patterns, it usually leads to the delay of high rank patterns generation, resulting in the slow growth of the support threshold and the mining efficiency. Aiming at this problem, a greedy-strategy-based top-rank-k frequent patterns hybrid mining algorithm (GTK) is proposed in this paper. In this algorithm, top-rank-k patterns are stored in a static doubly linked list called RSL, and the patterns are divided into short patterns and long patterns. The short patterns generated by a rank-first-search always joins the two patterns of the highest rank in RSL that have not yet been joined. On the basis of the short patterns satisfying specific conditions, the long patterns are extracted through level-wise-search. To reduce redundancy, GTK improves the generation method of subsume index and designs the new pruning strategies of candidates. This algorithm also takes the use of reasonable pruning strategies to reduce the amount of computation to improve the computational speed. Real datasets and synthetic datasets are adopted in experiments to evaluate the proposed algorithm. The experimental results show the obvious advantages in both time efficiency and space efficiency of GTK.


Cite This Article

Y. Long, W. Tang, B. Yang, X. Wang, H. Ma et al., "Gtk: a hybrid-search algorithm of top-rank-k frequent patterns based on greedy strategy," Computers, Materials & Continua, vol. 63, no.3, pp. 1445–1469, 2020.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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