Attribute reduction in concept lattice based on discernibility matrix

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3642 LNAI, Issue , 2005, Pages 157-165

  Zhang, Wen Xiu ^a   Wei, Ling ^a,b   Qi, Jian Jun ^a  

^a XI'AN JIAOTONG UNIVERSITY   (China)

^b NORTHWEST UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

DATA REDUCTION; FUNCTION EVALUATION; MATRIX ALGEBRA; PROBLEM SOLVING;

CONCEPT LATTICES; DISCERNIBILITY MATRIX; KNOWLEDGE DISCOVERY; KNOWLEDGE REDUCTIONS;

KNOWLEDGE BASED SYSTEMS;

EID: 33645987921     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11548706_17     Document Type: Conference Paper

References (15)

1. Wille, R.: Restructuring lattice theory: an approach based on hierarchies of concepts. In: Ivan Rival (ed.), Ordered sets, Reidel, Dordrecht-Boston (1982) 445-470
2. Hu, K.Y., Lu, Y.C., Shi, C.Y.: Advances in concept lattice and its application. Journal of Tsinghua University (Science & Technology), 40(9) (2000) 77-81
3. Ho, T.B.: An approach to concept formation based on formal concept analysis. IEICE Trans. Information and Systems, E782D(5) (1995) 553-559
4. Carpineto, C., Romano, G.: GALOIS: An order-theoretic approach to conceptual clustering. In: Utgoff, P. (ed.), Proceedings of ICML 293. Amherst, Elsevier (1993) 33-40
5. Godin, R.: Incremental concept formation algorithm based on Galois (concept) lattices. Computational Intelligence, 11(2) 1995 246-267
6. Oosthuizen, G.D.: The Application of Concept Lattice to Machine Learning. Technical Report, University of Pretoria, South Africa, (1996)
7. Yao, Y.Y.: Concept lattices in rough set theory. In: Dick, S., Kurgan, L., Pedrycz, W. and Reformat, M. (eds.), Proceedings of 2004 Annual Meeting of the North American Fuzzy Information Processing Society (NAFIPS 2004). IEEE Catalog Number: 04TH8736, June 27-30 (2004) 796-801
8. Oosthuizen, G.D.: Rough sets and concept lattices. In: Ziarko, W.P. (ed.), Rough Sets, and Fuzzy Sets and Knowledge Discovery (RSKD'93). London, Springer-Verlag (1994) 24-31
9. Deogun, J.S., Saquer, J.: Concept approximations for formal concept analysis. In: Stumme, G. (ed.), Working with Conceptual Structures. Contributions to ICCS 2000. Verlag Shaker Aachen (2000) 73-83
10. Düntsch, I., Gediga, G.: Algebraic aspects of attribute dependencies in information systems. Fundamenta Informaticae, 29(1-2) (1997) 119-133
11. Pagliani, P.: From concept lattices to approximation spaces: Algebraic structures of some spaces of partial objects. Fundamenta Informaticae, 18(1) (1993) 1-25
12. Grigoriev, P.A., Yevtushenko, S.A.: Elements of an Agile Discovery Environment. In: Grieser, G., Tanaka, Y. and Yamamoto, A. (eds.), Proc. 6th International Conference on Discovery Science (DS 2003). Lecture Notes in Artifical Intelligence, 2843 (2003) 309-316
13. Pawlak, Z.: Rough sets. International Journal of Computer and Information Sciences, 11 (1982) 341-356
14. Ganter, B., Wille, R.: Formal Concept Analysis, Mathematical Foundations. Springer, Berlin (1999)
15. Skowron, A., Rauszer, C.: The discernibility matrices and functions in information systems. In: Slowinski, R. (ed.), Intelligent Decision Support: Handbook of Applications and Advances of the Rough Set Theory. Kluwer Academic Publishers, Dordrecht (1992) 331-362