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A Novel Approach to Attribute Reduction in Concept Lattices

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Rough Sets and Knowledge Technology (RSKT 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4062))

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Abstract

Concept lattice is an effective tool for data analysis and knowledge discovery. Since one of the key problems of knowledge discovery is knowledge reduction, it is very necessary to look for a simple and effective approach to knowledge reduction. In this paper, we develop a novel approach to attribute reduction by defining a partial relation and partial classes to generate concepts and introducing the notion of meet-irreducible element in concept lattice. Some properties of meet-irreducible element are presented. Furthermore, we analyze characteristics of attributes and obtain sufficient and necessary conditions of the characteristics of attributes. In addition, we illustrate that adopting partial classes to generate concepts and the approach to attribute reduction are simpler and more convenient compared with current approaches.

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References

  1. Pawlak, Z.: Rough set. International Journal of Computer and Information Science 11, 341–356 (1982)

    Article  MATH  MathSciNet  Google Scholar 

  2. Wille, R.: Restructuring Lattice Theory: an Approach Based on Hierarchies of Concepts. In: Rival, I. (ed.) Ordered Sets, pp. 445–470. Reidel, Dordrecht, Boston (1982)

    Google Scholar 

  3. Ganter, B., Wille, R.: Formal Concept Analysis. Mathematical Foundations. Springer, New York (1999)

    MATH  Google Scholar 

  4. Ho, T.B.: An approximation to concept formation based on formal concept analysis. ŚIEICE Trans. Information and Systems 5, 553–559 (1995)

    Google Scholar 

  5. Carpineto, C., Romano, G.: GALOIS: an order-theoretic approach to conceptual clustering. In: Proceedings of ICML, Amherst, Elsevier, pp. 33–40. Elsevier, Amsterdam (1993)

    Google Scholar 

  6. Godin, R.: Incremental concept formation algorithm based on galois (concept) lattices. Computational Intelligence 2, 246–267 (1995)

    Article  Google Scholar 

  7. Yao, Y.Y.: Concept lattices in rough set theory. In: Proceedings of 23rd International Meeting of the North American Fuzzy Information Processing Society, pp. 796–801 (2004)

    Google Scholar 

  8. Yao, Y.: A Comparative Study of Formal Concept Analysis and Rough Set Theory in Data Analysis. In: Tsumoto, S., Słowiński, R., Komorowski, J., Grzymała-Busse, J.W. (eds.) RSCTC 2004. LNCS (LNAI), vol. 3066, pp. 59–68. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  9. Hu, K., Sui, Y., Lu, Y., Wang, J., Shi, C.: Concept approximation inconcept lattice, knowledge discovery and data mining. In: Cheung, D., Williams, G.J., Li, Q. (eds.) PAKDD 2001. LNCS (LNAI), vol. 2035, pp. 167–173. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  10. Saquer, J., Deogun, J.: Formal rough concept analysis. In: Zhong, N., Skowron, A., Ohsuga, S. (eds.) RSFDGrC 1999. LNCS (LNAI), vol. 1711, pp. 91–99. Springer, Heidelberg (1999)

    Chapter  Google Scholar 

  11. Saquer, J., Deogun, J.: Concept approximations based on rough sets and similarity measures. International. J. Appl. Math. Comput. Sci. 11, 655–674 (2001)

    MATH  MathSciNet  Google Scholar 

  12. Yao, Y.Y.: Rough set approximations in formal concept analysis. In: Proceedings of 2004 Annual Meeting of the North American Fuzzy Information Processing Society, pp. 73–78. IEEE, Los Alamitos (2004)

    Google Scholar 

  13. Osthuizen, G.D.: Rough sets and concept lattices. In: Proceedings of Rough Sets, and Fuzzy Sets and Knowledge Discovery (RSKD 1993), pp. 24–31. Springer, London (1994)

    Google Scholar 

  14. Zhang, W.X., Wei, L., Qi, J.J.: Attribute reduction in concept lattice based on discernibility matrix. In: Ślęzak, D., Wang, G., Szczuka, M., Düntsch, I., Yao, Y. (eds.) RSFDGrC 2005. LNCS (LNAI), vol. 3641, pp. 157–165. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  15. Shao, M.W., Zhang, W.X.: Approximation in formal concept analysis. In: Ślęzak, D., Wang, G., Szczuka, M., Düntsch, I., Yao, Y. (eds.) RSFDGrC 2005. LNCS (LNAI), vol. 3641, pp. 43–52. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  16. Wolski, W.: Formal Concept Analysis and Rough Set Theory from the Perspective of Finite Topological Approximations. In: Peters, J.F., Skowron, A. (eds.) Transactions on Rough Sets III. LNCS, vol. 3400, pp. 230–243. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

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Wang, X., Ma, J. (2006). A Novel Approach to Attribute Reduction in Concept Lattices. In: Wang, GY., Peters, J.F., Skowron, A., Yao, Y. (eds) Rough Sets and Knowledge Technology. RSKT 2006. Lecture Notes in Computer Science(), vol 4062. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11795131_76

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  • DOI: https://doi.org/10.1007/11795131_76

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-36297-5

  • Online ISBN: 978-3-540-36299-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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