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基于 Rough Set 的知识发现系统 被引量：2

KNOWLEDGE DISCOVERY SYSTEMS BASED ON ROUGH SET THEORY
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摘要 ＲｏｕｇｈＳｅｔ理论是近年来出现的处理模糊和不确定性的数学工具，已广泛应用于人工智能的许多领域特别是ＫＤＤ领域。文章介绍了ＲｏｕｇｈＳｅｔ理论的基本思想，并着重讨论了几个基于ＲｏｕｇｈＳｅｔ理论的典型ＫＤＤ系统。 Rough Set theory is a new mathematical tool to deal with vagueness and uncertainty. This paper introduces the basic idea and characteristics of Rough Set theory.Several representative systems based on Rough Set theory are analyzed.
作者 胡可云 王志海 徐本柱
机构地区 合肥工业大学
出处 《合肥工业大学学报（自然科学版）》 CAS CSCD 1998年第1期71-74,共4页 Journal of Hefei University of Technology：Natural Science
基金 国家教委博士点专项科研基金 安徽省自然科学基金
关键词 ROUGHSET 知识发现 数据库知识发现 人工智能 Rough Set, knowledge discovery,knowledge disovery of database(KDD)
分类号 TP18 [自动化与计算机技术—控制理论与控制工程]
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参考文献4

  • 1Pawlak Z. Rough sets: theoretical aspects of reasoning about data. Dordrecht : Kluwer Acasemic Publishers, 1991.
  • 2Grzymala-Bausse J W. LERS: a system of knowledge discovery based on rough sets. In: Tsumoto S,ed. Proc of 5th Int. Workshop RSFD'96. Tokyo:Morgan Kanfmann RSFD. 1996. 443-444.
  • 3Ziarko'W, Shan N. KDD-R: a comprehensive system for knowledge discovery in databases using rough sets. In:Lin T Y, Wildberger A M,eds. Soft Computing . San Diego:Simulation Councils Inc, 1995. 298-301.
  • 4Slowinski R, Stefanowski J. 'RoughDAS' and 'RoughClass' software implementations of the rough sets approach.In: Slowinski R,ed. Intelligent Decision Support: Handbook of Applications and Advances of Rough Sets Theory.Dordrecht: Kluwer Acasemic Publishers, 1992. 445-456.

同被引文献33

  • 1PAWLAK Z. Rough sets[J]. Information and Computer Science, 1982, 11(5): 341-356.
  • 2PAWLAK Z. Rough Sets-Theoretical Aspects of Reasoning About Data[M]. London:Kluwer Academic Publishing Company, 1991.
  • 3PAWLAK Z, GRZYMALA-BUSSE J W, SLOWINSKI R. Rough sets[J]. Communications of the ACM, 1995, 38(11): 89-95.
  • 4GRZYMALA-BUSSE J W. Knowledge acquisition under uncertainty-A rough set approach[J]. J Intel Rob Syst, 1998, 1: 3-16.
  • 5CHMIELEW M R, GRZYMALA-BUSSE J W. Global discretization of continuous attributes as preprocessing for machine learning[J]. International Journal of Approximate Reasoning, 1996, 15: 319-331.
  • 6CHAN C C. A rough set approach to attribute generalization in data mining[J]. Journal of Information Sciences, 1998, 10(7): 169-176.
  • 7LINGRAS P J, YAO Y Y. Data mining using extensions of the rough set model[J]. Journal of the American Society for Information Science, 1998, 49(5): 415-422.
  • 8PAWLAK Z, SLOWINSKI R. Rough set approach to multi-attribute decision analysis[J]. Invited Review, Eur J of Oper Res, 1994, 72: 443-459.
  • 9MCSHERRY D. Knowledge discovery by inspection[J]. Decision Support Systems, 1997, 21: 43-47.
  • 10PAWLAK Z. Rough set approach to knowledge-based decision support[J]. European Journal of Operational Research, 1997, 99: 48-57.

引证文献2

二级引证文献13

合肥工业大学学报（自然科学版）
1998年 第1期

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