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Vol. 156, Issue 9, September 2013, pp. 351-359




A Frequent Pattern Mining Algorithm Based on Concept Lattice
1, 2, 3 Changsheng Zhang, 4 Jing Ruan, 3,* Haijiang Xia, 3 Hailong Huang, 1 Bingru Yang

1 School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, BJ10, China

2 Beijing Key Laboratory of Knowledge Engineering for Materials Science, Beijing, BJ10, China

3 College of Physics & Electronic Information Engineering, Wenzhou University, Zhejiang, ZJ577, China

4 Wenzhou Vocational & Technical College, Zhejiang, ZJ577, China

1 Tel.: 0086-0577-86590275, fax: 0086-0577-86689010
E-mail: jsj_zcs@126.com, ruanjing1979@126.com, 156732998@qq.com, hhl@wzu.edu.cn, bryang_kd@yahoo.com.cn


Received: 5 June 2013   /Accepted: 25 August 2013   /Published: 30 September 2013

Digital Sensors and Sensor Sysstems


Abstract: The concept lattice is an effective tool for data analysis and rule extraction, it is often well to mine frequent patterns by making use of concept lattice. In this paper, a frequent itemset mining algorithm FPCL based on concept lattice which builds lattice in batches, the algorithm builds lattice down layer by layer through the layer concept nodes and temporary nodes based on hierarchical concept lattice; and seeks up the parent-child relationship upward concept nodes layer by layer, which can be generated the Hasse diagram with the inter-layer connection. In addition, in the process of the generation of each lattice node, we do the dynamic pruning for the concept lattice based on the minimum support degree and relevant properties, and delete a large number of non-frequent, repeat and containing nodes, such that redundant lattice nodes do not generate, thus the space and time complexities of the algorithm are greatly enhanced. The experimental results show that the algorithm has a good performance.


Keywords: Data mining, Frequent itemset, Concept lattice, Dynamic pruning.



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