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International Conference on Intelligent Computing

ICIC 2011: Bio-Inspired Computing and Applications pp 690–698Cite as

Closed-Label Concept Lattice Based Rule Extraction Approach

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Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 6840))

Abstract

Concept lattice is an effective tool for data analysis and extracting classification rules. However, the classical concept lattice often produce a lot of redundant rules. Closed-label concept lattice realizes reduction of concept intention, which can be used to extract fewer rules than the classical concept lattice. This paper presents a method for classification rules extraction based on the closed-label concept lattice. Examples show that the proposed method is effective for extracting more concise classification rules.

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Author information

Authors and Affiliations

  1. School of Computer and Information Technology, Shanxi University, Taiyuan, 030006, Shanxi, China

    Junhong Wang & Jiye Liang

  2. Key Laboratory of Computational Intelligence and Chinese Information Processing, Ministry of Education, Taiyuan, 030006, China

    Yuhua Qian

Authors
  1. Junhong Wang
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  2. Jiye Liang
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  3. Yuhua Qian
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Editor information

Editors and Affiliations

  1. School of Electronics and Information Engineering, Tongji University, 4800 Caoan Road, 201804, Shanghai, China

    De-Shuang Huang

  2. School of Computer and Communication Engineering, Zhengzhou University of Light Industry, No. 5, Dongfeng Road, Jinshui District, 450002, Zhengzhou, Henan, China

    Yong Gan

  3. School of Electrical, Computer & Telecommunications Engineering, University of Wollongong, 2522, P.O. Box, North Wollongong, NSW, Australia

    Prashan Premaratne

  4. School of Computer Science and Engineering, Inha University, 402-751, Inchon, Korea

    Kyungsook Han

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© 2012 Springer-Verlag Berlin Heidelberg

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Cite this paper

Wang, J., Liang, J., Qian, Y. (2012). Closed-Label Concept Lattice Based Rule Extraction Approach. In: Huang, DS., Gan, Y., Premaratne, P., Han, K. (eds) Bio-Inspired Computing and Applications. ICIC 2011. Lecture Notes in Computer Science(), vol 6840. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24553-4_91

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  • DOI: https://doi.org/10.1007/978-3-642-24553-4_91

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24552-7

  • Online ISBN: 978-3-642-24553-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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