Abstract
In this paper we present a novel approach to the concept approximations in concept lattice. Using the similar idea of rough set theory and unique properties of concept lattice, upper and lower approximations of any object or attribute set can be found by exploiting meet-(union-)irreducible elements in concept lattice, the approximations can be performed on the fly. We show that our approach is more natural and effective than existing approach.
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References
R.E. Kent, Rough Concept Analysis: A synthesis of rough set and formal concept analysis, Fundamenta Informaticae, 27 (1996):169–181
J. Saquer, J.S. Deogun, Formal rough concept analysis, N. Zhong, A. Skowron and S. Ohsuga (eds.) Proceedings of RSFDGrC’99, Japan, Springer, 1999, 91–99
B. Ganter, R. Wille, Formal concept analysis: mathematical foundations. Berlin: Springer, 1999.
K. Hu, Y. Lu, L. Zhou, C. Shi, Integrated classification and association rule mining based on concept lattice, N. Zhong, A. Skowron, and S. Ohsuga (eds.) Proceedings of RSFDGrC’99, Japan, Springer, 1999.443–447
K. Hu, Y. Lu, C. Shi. Incremental association rule mining: a concept lattice approach[A]. in Ning Z, Lizhu Z. Eds. Proceedings of PAKDD’99. Beijing, Springer, 1999.109–113
Z. Pawlak, Rough sets-theoretical aspects of reasoning about data, Kluwer publishers, Boston, Dordrecht, 1991
Eklund PW, Martin P. WWW indexation and document navigation using conceptual structures. 2nd IEEE Conference on Intelligent Information Processing Systems (ICIPS’ 98), IEEE Press, 1998, 217–221
Godin R, Mineau G, Missaoui R, St-Germain M, Faraj N. Applying concept formation methods to software reuse. International Journal of Software Engineering and Knowledge Engineering, 5(1), 119–142.
Godin R. Incremental concept formation algorithm based on Galois (concept) lattices. Computational Intelligence, 11(2) (1995) 246–267
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© 2001 Springer-Verlag Berlin Heidelberg
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Hu1, K., Sui, Y., Lu, Y., Wang, J., Shi, C. (2001). Concept Approximation in Concept Lattice. In: Cheung, D., Williams, G.J., Li, Q. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2001. Lecture Notes in Computer Science(), vol 2035. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45357-1_21
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DOI: https://doi.org/10.1007/3-540-45357-1_21
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