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Proceedings Paper

Association rule mining based on concept lattice
Author(s): Kun Qin; Zequn Guan; Deren Li; Xinzhou Wang; Qizhi Xiao
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Paper Abstract

From the view of concept formation, the paper researched the theories and methods of data mining based on concept lattice theory. The process of knowledge discovery from database may be understood as the process of concept formation from database. The concept lattice theory provides such a formal tool to reflect the process of concept formation. Through this theory, the intension and extension can be formal expressed, the analysis objects can be converted to formal context, and from these formal contexts, the concepts in different hierarchies and their relations can be extracted, and the aim of data mining can be achieved. The algorithm of association rule mining includes two steps: the construction of concept lattice and the production of association rule. The paper produced a fast construction algorithm of incremental concept lattice based on indexed tree. The actual experiment results proved: the algorithm of this paper is faster and more efficient than the traditional association rule mining algorithms-Apriori algorithms, and the algorithm can automated delete the redundant rules, can carry the aim of association rule automated simplified.

Paper Details

Date Published: 2 December 2005
PDF: 14 pages
Proc. SPIE 6045, MIPPR 2005: Geospatial Information, Data Mining, and Applications, 60450W (2 December 2005); doi: 10.1117/12.650388
Show Author Affiliations
Kun Qin, Wuhan Univ. (China)
Zequn Guan, Wuhan Univ. (China)
Deren Li, Wuhan Univ. (China)
Xinzhou Wang, Wuhan Univ. (China)
Qizhi Xiao, Wuhan Univ. (China)

Published in SPIE Proceedings Vol. 6045:
MIPPR 2005: Geospatial Information, Data Mining, and Applications
Jianya Gong; Qing Zhu; Yaolin Liu; Shuliang Wang, Editor(s)

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