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Attribute Reduction of Lattice-Value Information System Based on L-Dependence Spaces

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Fuzzy Information & Engineering and Operations Research & Management

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 211))

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Abstract

Lattice is a wide concept. All different kinds of information systems come down to lattice-value information system. Attribute reduction of different kinds of information systems could be boiled down to that of lattice-value information systems. In this paper, L-dependence space is established on lattice-value information system. Then attribute reduction of theory and algorithm is put forward and the effectiveness and feasibility of algorithm are explained by an example. Finally, the result of attribute reduction is compared with other algorithms by computational complexity.

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References

  1. Novotny, M., Pawlak, Z.: On a problem concerning dependence spaces. Fundamenta Informaticae 16, 275–287 (1992)

    MathSciNet  MATH  Google Scholar 

  2. Novotny, M., Pawlak, Z.: Independence of attributes. Bull. Polish Acad. Sci. Math. 36, 459–465 (1988)

    MathSciNet  MATH  Google Scholar 

  3. Novotny, M.: Dependence spaces of information systems. In: Orlowska, E. (ed.) Logical and algebra-ic investigations in rough set theory (to appear)

    Google Scholar 

  4. Belohlavek, R.: Concept lattices and order in fuzzy logic. Ann. Pure Appl. Logic 128, 277–298 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  5. 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)

    Chapter  Google Scholar 

  6. Yao, Y.Y.: Concept lattices in rough set theory. In: Proceedings of 23rd International Meeting of the North American Fuzzy Information Processing Society, pp. 796–800 (2004)

    Google Scholar 

  7. Zhang, W.-X., Wei, L., Qi, J.-J.: Attribute reduction in concept lattice based on discernibilit-y matrix. In: Slezak, D. et al. (eds.): RSFDGrC 2005, LNAI 3642, pp. 157–165 (2005)

    Google Scholar 

  8. Zhang, W.-X., Mi, J.-S., Wu, W.-Z.: Approaches to knowledge reduction in inconsistent syst-ems. Int. J. Intell. Syst. 18, 989–1000 (2003)

    Article  MATH  Google Scholar 

  9. Zedeh, L.A.: Fuzzy sets. Inf. Control 8, 338–353 (1965)

    Article  Google Scholar 

  10. Yager, R.R.: An approach to ordinal decision making. Int. J. Approximate Reasoning 12, 237–261 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  11. Liang, J.-Y., Xu, Z.-B.: The algorithm on knowledge reduction in incomplete information systems. Int. J. Uncertainty Fuzziness Knowl. Based Syst. 10(1), 95–103 (2002)

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgments

Thanks to the support by National Natural Science Foundation of China (No. 11071178 ).

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Correspondence to Chang Shu .

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Shu, C., Mo, Zw., Tang, X., Zhang, Zh. (2014). Attribute Reduction of Lattice-Value Information System Based on L-Dependence Spaces. In: Cao, BY., Nasseri, H. (eds) Fuzzy Information & Engineering and Operations Research & Management. Advances in Intelligent Systems and Computing, vol 211. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38667-1_12

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  • DOI: https://doi.org/10.1007/978-3-642-38667-1_12

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  • Online ISBN: 978-3-642-38667-1

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