A Rough Set Approach to Information Systems Decomposition

被引:1
|
作者
Pancerz, Krzysztof [1 ,2 ]
Suraj, Zbigniew [3 ]
机构
[1] Univ Management & Adm, PL-22400 Zamosc, Poland
[2] Univ Informat Technol & Management, Inst Biomed Informat, PL-35225 Rzeszow, Poland
[3] Univ Rzeszow, Inst Comp Sci, PL-35310 Rzeszow, Poland
关键词
decomposition; information analysis; information system; knowledge representation; machine learning; reduct; rough sets; CLASSIFICATION; MODELS;
D O I
10.3233/FI-2013-908
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
The aim of this paper is to present the methods and algorithms of information systems decomposition. In the paper, decomposition with respect to reducts and the so-called global decomposition are considered. Moreover, coverings of information systems by components are discussed. An essential difference between two kinds of decomposition can be observed. In general, global decomposition can deliver more components of a given information system. This fact can be treated as some kind of additional knowledge about the system. The proposed approach is based on rough set theory. To demonstrate the usefulness of this approach, we present an illustrative example coming from the economy domain. The discussed decomposition methods can be applied e. g. for design and analysis of concurrent systems specified by information systems, for automatic feature extraction, as well as for control design of systems represented by experimental data tables.
引用
收藏
页码:257 / 272
页数:16
相关论文
共 50 条
  • [1] An approach to rough set decomposition of incomplete information systems
    Qizhong, Zhang
    ICIEA 2007: 2ND IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS, VOLS 1-4, PROCEEDINGS, 2007, : 2455 - 2460
  • [2] Rough set approach to incomplete information systems
    Kryszkiewicz, M
    INFORMATION SCIENCES, 1998, 112 (1-4) : 39 - 49
  • [3] Information Systems and Rough Set Approximations: An Algebraic Approach
    Khan, Md Aquil
    Banerjee, Mohua
    PATTERN RECOGNITION AND MACHINE INTELLIGENCE, 2011, 6744 : 339 - 344
  • [4] Conflict analysis and information systems: A rough set approach
    Skowron, Andrzej
    Ramanna, Sheela
    Peters, James F.
    ROUGH SETS AND KNOWLEDGE TECHNOLOGY, PROCEEDINGS, 2006, 4062 : 233 - 240
  • [5] Multiple granulation rough set approach to ordered information systems
    Xu, Weihua
    Sun, Wenxin
    Zhang, Xiaoyan
    Zhang, Wenxiu
    INTERNATIONAL JOURNAL OF GENERAL SYSTEMS, 2012, 41 (05) : 475 - 501
  • [6] Knowledge acquisition in incomplete information systems: A rough set approach
    Leung, Y
    Wu, WZ
    Zhang, WX
    EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2006, 168 (01) : 164 - 180
  • [7] A new rough set approach to knowledge discovery in incomplete information systems
    Wu, WZ
    Mi, JS
    Zhang, WX
    2003 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-5, PROCEEDINGS, 2003, : 1713 - 1718
  • [8] Dominance-Based Rough Set Approach for Possibilistic Information Systems
    Fan, Tuan-Fang
    Liau, Churn-Jung
    Liu, Duen-Ren
    ROUGH SETS, FUZZY SETS, DATA MINING AND GRANULAR COMPUTING, RSFDGRC 2011, 2011, 6743 : 119 - 126
  • [9] Rough set approach under dynamic granulation in incomplete information systems
    Qian, Yuhua
    Liang, Jiye
    Zhang, Xia
    Dang, Chuangyin
    MICAI 2007: ADVANCES IN ARTIFICIAL INTELLIGENCE, 2007, 4827 : 1 - +
  • [10] Dynamic variable precision rough set approach for probabilistic set-valued information systems
    Huang, Yanyong
    Li, Tianrui
    Luo, Chuan
    Fujita, Hamido
    Horng, Shi-jinn
    KNOWLEDGE-BASED SYSTEMS, 2017, 122 : 131 - 147