Abstract
In this paper we investigate the dynamic characteristics in an incomplete decision system while information is increasing. We modify the definition of reduction of condition attributes in this case, and present algorithms of reduction in order to deal with increase information.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
References
Kryszkiewicz, M.: Rough Set Approach to Incomplete Information Systems. Information Science 112(1-4), 39–49 (1998)
Kryszkiewicz, M.: Rules in Incomplete Information Systems. Information Science 113(3-4), 271–292 (1999)
Grzymała-Busse, J.W., Hu, M.: A Comparison of Several Approaches to Missing Attribute Values in Data Mining. In: Ziarko, W., Yao, Y. (eds.) RSCTC 2000. LNCS (LNAI), vol. 2005, pp. 378–385. Springer, Heidelberg (2001)
Grzymała-Busse, J.W.: Characteristic Relations for Incomplete Data: A Generalization of the Indiscernibility Relation. In: Tsumoto, S., et al. (eds.) RSCTC 2004. LNCS (LNAI), vol. 3066, pp. 244–253. Springer, Heidelberg (2004)
Grzymała-Busse, J.W.: Incomplete Data and Generalization of Indiscernibility Relation, Definability, and Approximations. In: Ślęzak, D., et al. (eds.) RSFDGrC 2005. LNCS (LNAI), vol. 3641, pp. 244–253. Springer, Heidelberg (2005)
Stefanowski, J., Tsoukiàs, A.: On the Extension of Rough Sets under Incomplete Information. In: Zhong, N., Skowron, A., Ohsuga, S. (eds.) RSFDGrC 1999. LNCS (LNAI), vol. 1711, pp. 73–82. Springer, Heidelberg (1999)
Stefanowski, J., Tsoukiàs, A.: Incomplete Information Tables and Rough Classification. Computational Intelligence 17(3), 545–566 (2001)
Greco, S., Matarazzo, B., Slowinski, R.: Dealing with Missing Data in Rough Set Analysis of Multi-attribute and Multi-criteria Decision Problems. In: Zanakis, S.H., Doukidis, G., Zopounidis, Z. (eds.) Decision Making: Recent developments and Worldwide Applications, pp. 295–316. Kluwer Academic Publishers, Dordrecht (2000)
Wang, G.Y.: Extension of Rough Set Under Incomplete Information Systems (in Chinese). Journal of Computer Research and Development 39(10), 1238–1243 (2002)
Wang, G.Y.: Rough Set Theory and Knowledge Discovery (in Chinese). Xi’an Jiaotong University Press, Xi’an (2001)
Pawlak, Z.: Rough sets-Theoretical Aspect of Reasoning about Data. Kluwer Academic Publishers, Dordrecht (1991)
Liu, Q.: Rough Sets and Rough Reasoning. Science Press, Beijing (2001)
Cattaneo, G., Ciucci, D.: Investigation about Time Monotonicity of Similarity and Preclusive Rough Approximations in Incomplete Information Systems. In: Tsumoto, S., et al. (eds.) RSCTC 2004. LNCS (LNAI), vol. 3066, pp. 38–48. Springer, Heidelberg (2004)
Liu, S.H., Sheng, Q.J., Shi, Z.Z.: A New Method for Fast Computing Positive Region (in Chinese). Journal of Computer Research and Development 40(5), 637–642 (2003)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Deng, D., Huang, H. (2007). Dynamic Reduction Based on Rough Sets in Incomplete Decision Systems. In: Yao, J., Lingras, P., Wu, WZ., Szczuka, M., Cercone, N.J., Ślȩzak, D. (eds) Rough Sets and Knowledge Technology. RSKT 2007. Lecture Notes in Computer Science(), vol 4481. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72458-2_9
Download citation
DOI: https://doi.org/10.1007/978-3-540-72458-2_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72457-5
Online ISBN: 978-3-540-72458-2
eBook Packages: Computer ScienceComputer Science (R0)