Abstract
Normally, in some complex information systems, the binary relation on domain of any attribute is just a kind of ordinary binary, which does not meet some common properties such as reflexivity, transitivity or symmetry. In view of the above-mentioned facts this paper attempts to employ FCA(Formal Concept Analysis), proposes a rough set model based on FCA, in which equivalence relations, dominance relations, similarity relations(or tolerance relations) and neighborhood relations on universe are expanded to general binary relations and problems in rough set theory are discussed based on FCA. Particularly, from the above description of complex information systems, we can see that the relation in domain of any attribute may be extremely complex, which often leads to high time complexity and space complexity in the process of knowledge acquisition. For above reason this paper introduces granular computing(GrC), which can effectively reduce the complexity to a certain extent.
This is a preview of subscription content, log in via an institution.
References
Ganter, B., Wille, R.: Formal Concept Analysis: Mathematical Foundations. Springer, Berlin (1999)
Greco, S., Matarazzo, B., Slowinski, R.: Rough approximation of a preference relation by dominance relation. Eur. J. Oper. Res. 117, 63–83 (1999)
Kang, X.P., Li, D.Y., Wang, S.G., Qu, K.S.: Rough set model based on formal concept analysis. Inf. Sci. 222, 611–625 (2013)
Leung, Y., Li, D.Y.: Maximal consistent block technique for rule acquisition in incomplete information systems. Inf. Sci. 153, 85–106 (2003)
Mi, J.S., Leung, Y., Wu, W.Z.: Approaches to attribute reduct in concept lattices induced by axialities. Knowl.-Based Syst. 23, 504–511 (2010)
Pawlak, Z.: Rough sets. Int. J. Comput. Inform. Sci. 11, 341–356 (1982)
Saaty, T.L.: A scaling method for priorities in hierarchical structures. J. Math. Psychol. 15(3), 234–281 (1977)
Slowinski, R., Vanderpooten, D.: A generalized definition of rough approximations based on similarity. Knowl. Data Eng. 12, 331–336 (2000)
Wei, L., Qi, J.J.: Relation between concept lattice reduct and rough set reduct. Knowl.-Based Syst. 23, 934–938 (2010)
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)
Acknowledgments
We would like to thank anonymous reviewers very much for their professional comments and valuable suggestions. This work was supported by the National Postdoctoral Science Foundation of China (No. 2014M560352) and the National Natural Science Foundation of China (No. 61273304).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Kang, X., Miao, D., Jiao, N. (2015). A Knowledge Acquisition Model Based on Formal Concept Analysis in Complex Information Systems. In: Yao, Y., Hu, Q., Yu, H., Grzymala-Busse, J.W. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. Lecture Notes in Computer Science(), vol 9437. Springer, Cham. https://doi.org/10.1007/978-3-319-25783-9_26
Download citation
DOI: https://doi.org/10.1007/978-3-319-25783-9_26
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-25782-2
Online ISBN: 978-3-319-25783-9
eBook Packages: Computer ScienceComputer Science (R0)