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Two Types of Generalized Variable Precision Formal Concepts

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Rough Sets and Intelligent Systems Paradigms (RSEISP 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4585))

Abstract

In this paper, we introduce two pairs operators in fuzzy formal contexts. Based on the proposed operators, we present two types of generalized variable precision formal concepts, i.e. property oriented crisp-fuzzy concepts and object oriented fuzzy-crisp concepts. We have different level generalized formal concepts with different precision level. Last, we discuss the relationship between different precision level generalized concepts lattices in details.

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References

  1. 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 

  2. Gediga, B., Wille, R.: Formal Concept Analysis. Mathematic Foundations. Springer, Berlin (1999)

    Google Scholar 

  3. Carpineto, C., Romano, G.: A lattice conceptual clustering system and its application to browsing retrieval. Mach. Learning 10, 95–122 (1996)

    Google Scholar 

  4. Faid, M., Missaoi, R., Godin, R.: Mining complex structures using context concatenation in formal concept analysis. International KRUSE Symposium, Vancouver, BC (August 11–13, 1997)

    Google Scholar 

  5. Godin, R., Missaoi, R.: An incremental concept formation approach for learning from databases. Theoret. Comput. Sci. 133, 387–419 (1994) (special issues on Formal Methods in Databases and Software Engineering)

    Article  MATH  MathSciNet  Google Scholar 

  6. Harms, S.K., Deogum, J.S.: Sequential association rule mining with time lags. J. Intell. Inform. Systems 22(1), 7–22 (2004)

    Article  Google Scholar 

  7. Wille, R.: Knowledge acquisition by methods of formal concept analysis. In: Diday, E. (ed.) Data Analysis, Learning Symbolic and Numeric Knowledge, Nova Science, pp. 365–380 (1989)

    Google Scholar 

  8. Burusco, A., Fuentes-Gonzalez, R.: Concept lattices defined from implication operators. Fuzzy Sets and systems 114(3), 431–436 (1998)

    Article  MathSciNet  Google Scholar 

  9. Elloumi, S., Jaam, J., Hasnah, A., Jaoua, A., Nafkha, I.: A multi-level conceptual data reduction approach based on the Lukasiewicz implication. Information Sciences 163, 253–262 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  10. Belohlavek, R.: Fuzzy closure operators. I. J. Math. Anal. Appl. 262, 473–489 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  11. Belohlavek, R.: Concept lattice and order in fuzzy logic. Annals of pure and Apll. Logic 128(1-3), 277–298 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  12. Popescu, A.: A general approach to fuzzy concept. Math. Logic Quaterly 50(3), 1–17 (2001)

    Google Scholar 

  13. Georgescu, G., Popescu, A.: Non-dual fuzzy connections. Archive for Mathematic Logic 43(8), 1009–1039 (2004)

    MATH  MathSciNet  Google Scholar 

  14. Elloumi, S., Jaoua, A.: Automatic classification using fuzzy concepts. In: Proc. JCIS, Atlantic City, vol. 1, pp. 276C279 (2000)

    Google Scholar 

  15. Jaoua, A., Elloumi, S.: Galois connection, formal concepts and Galois lattice in real relations: application in a real classifier. The Journal of Systems and Software 60, 149–163 (2002)

    Article  Google Scholar 

  16. Fan, S.Q.: Fuzzy Concept Lattice and Variable Precision Concept Lattice, Ph. M. Thesis, Faculty of Science, Xi’an Jiaotong University (2006)

    Google Scholar 

  17. Yao, Y.Y.: A comparative study of formal concept analysis and rough set theory in Data analysis, Rough Sets and Current Trends in Computing. In: RSCT’04. Proceedings of 3rd International Conference (2004)

    Google Scholar 

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

    Google Scholar 

  19. Gediga, G., Duntsch, I.: Modal-style operators in qualitative data analysis. In: Proceedings of the 2002 IEEE International Conference on Data Mining, pp. 155–162. IEEE Computer Society Press, Los Alamitos (2002)

    Google Scholar 

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Authors and Affiliations

  1. Faculty of Science, Xi’an Jiaotong University, Xi’an, Shaan’xi 710049, P.R. China

    Hong-Zhi Yang

  2. Pingyuan University, Xinxiang, Henan Province 453003, P.R. China

    Hong-Zhi Yang

  3. School of Information Technology, Jiangxi University of Finance & Economics, Nanchang, Jiangxi 330013, P.R. China

    Ming-Wen Shao

  4. Jiangxi Key Laboratory of Data and Knowledge Engineering, Jiangxi University of Finance & Economics, Nanchang, Jiangxi 330013, P.R. China

    Ming-Wen Shao

Authors
  1. Hong-Zhi Yang
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  2. Ming-Wen Shao
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Editor information

Marzena Kryszkiewicz James F. Peters Henryk Rybinski Andrzej Skowron

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© 2007 Springer-Verlag Berlin Heidelberg

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Yang, HZ., Shao, MW. (2007). Two Types of Generalized Variable Precision Formal Concepts. In: Kryszkiewicz, M., Peters, J.F., Rybinski, H., Skowron, A. (eds) Rough Sets and Intelligent Systems Paradigms. RSEISP 2007. Lecture Notes in Computer Science(), vol 4585. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73451-2_69

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  • DOI: https://doi.org/10.1007/978-3-540-73451-2_69

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73450-5

  • Online ISBN: 978-3-540-73451-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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