Abstract
Object oriented concept lattices and property oriented concept lattices are two kinds of concept lattices and belong to formal concept analysis. In the theory of formal concept analysis, attribute reduction is one of basic problems, it can make the discovery of implicit knowledge in data easier and the representation simpler. Different attributes play different roles in reduction theory. This paper studies the attribute characteristics of object oriented concept lattices, and gives equivalent conditions for each kind of attribute characteristics. Finally, the paper shows that there are the same attribute characteristics for both object oriented concept lattices and property oriented concept lattices, so, study each one of them can obtain the other’s information.
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References
Wille, R.: Restructuring lattice theory: an approach based on hierarchies of concept, ordered sets. In: Rival, I. (ed.), pp. 445–470. Reidel, Dordrecht (1982)
Godin, R.: Incremental concept formation algorithm based on Galois lattices. Comput. Intell. 11(2), 246–267 (1999)
Saquer, J., Deogun, J.S.: Formal Rough Concept Analysis. In: Zhong, N., Skowron, A., Ohsuga, S. (eds.) RSFDGrC 1999. LNCS (LNAI), vol. 1711, pp. 91–99. Springer, Heidelberg (1999)
Kent, R.E., Bowman, C.M.: Digital Libraries, Conceptual Knowledge Systems and the Nebula Interface. Technical Report, University of Arkansas (1995)
Sutton, A., Maletic, J.I.: Recovering UML class models from C++: a detailed explanation. Inf. Softw. Technol. 48(3), 212–229 (2007)
Ganter, B., Stumme, G., Wille, R.: Formal Concept Analysis: Foundations and Applications. Springer, Heidelberg (2005)
Zhang, W.X., Wei, L., Qi, J.J.: Attribute reduction theory and approach to concept lattice. Science in China Series F-Information Science 48(6), 713–726 (2005)
Wang, X., Ma, J.-M.: A Novel Approach to Attribute Reduction in Concept Lattices. In: Wang, G.-Y., Peters, J.F., Skowron, A., Yao, Y. (eds.) RSKT 2006. LNCS (LNAI), vol. 4062, pp. 522–529. Springer, Heidelberg (2006)
Liu, M.Q., Wei, L., Zhao, W.: The Reduction Theory of Object Oriented Concept Lattices and Property Oriented Concept Lattices. In: Wen, P., Li, Y., Polkowski, L., Yao, Y., Tsumoto, S., Wang, G. (eds.) RSKT 2009. LNCS, vol. 5589, pp. 587–593. Springer, Heidelberg (2009)
Wei, L., Zhang, X.-H., Qi, J.-J.: Granular Reduction of Property-Oriented Concept Lattices. In: Croitoru, M., Ferré, S., Lukose, D. (eds.) ICCS 2010. LNCS, vol. 6208, pp. 154–164. Springer, Heidelberg (2010)
Pawlak, Z.: Rough sets. International Journal of Computer and Information Science 11, 341–356 (1982)
Düntsch, I., Gediga, G.: Approximation Operators in Qualitative Data Analysis. In: de Swart, H., Orłowska, E., Schmidt, G., Roubens, M. (eds.) TARSKI 2003. LNCS, vol. 2929, pp. 214–230. Springer, Heidelberg (2003)
Gediga, G., Duntsch, I.: Modal-style operations in qualitative data analysis. In: Proceedings of the 2002 IEEE International Conference on Data Mining, pp. 155–162 (2002)
Yao, Y.Y.: Concept lattices in rough set theory. In: Dick, S., Kurgan, L., Pedrycz, W., Reformat, M. (eds.) Proceedings of 2004 Annual Meeting of the North American Fuzzy Information Processing Society, June 27-30, pp. 796–801 (2004)
Ganter, B., Wille, R.: Formal Concept Analysis, Mathematical Foundations. Springer, Berlin (1999)
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Wei, L., Liu, MQ. (2012). Attribute Characteristics of Object (Property) Oriented Concept Lattices. In: Yao, J., et al. Rough Sets and Current Trends in Computing. RSCTC 2012. Lecture Notes in Computer Science(), vol 7413. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32115-3_40
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DOI: https://doi.org/10.1007/978-3-642-32115-3_40
Publisher Name: Springer, Berlin, Heidelberg
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