Extension of rough set under incomplete information systems

被引:0
|
作者
Wang, GY [1 ]
机构
[1] Chongqing Univ Posts & Telecommun, Inst Comp Scif & Technol, Chongqing 400065, Peoples R China
关键词
rough set; indiscernibility relation; tolerance relation; similarity relation; valued tolerance relation; limited tolerance relation;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The classical rough set theory developed by professor Pawlak is based on complete information systems. It classifies objects using upper-approximation and lower-approximation defined on an indiscernibility relation that is a kind of equivalent relation. In order to process incomplete information systems, the classical rough set theory needs to be extended, especially, the indiscernibility relation needs to be extended to some inequivalent relation. There are several extensions for the indiscernibility relation at present, such as tolerance relation, non-symmetric similarity relation, and valued tolerance relation. Unfortunately, these extensions have their own limitation. In this paper, we will develop a new extension of rough set that is based on a limited tolerance relation.
引用
收藏
页码:1098 / 1103
页数:6
相关论文
共 50 条
  • [1] On the extension of rough sets under incomplete information
    Stefanowski, J
    Tsoukiàs, A
    [J]. NEW DIRECTIONS IN ROUGH SETS, DATA MINING, AND GRANULAR-SOFT COMPUTING, 1999, 1711 : 73 - 81
  • [2] Rough set approach under dynamic granulation in incomplete information systems
    Qian, Yuhua
    Liang, Jiye
    Zhang, Xia
    Dang, Chuangyin
    [J]. MICAI 2007: ADVANCES IN ARTIFICIAL INTELLIGENCE, 2007, 4827 : 1 - +
  • [3] Rough set approach to incomplete information systems
    Kryszkiewicz, M
    [J]. INFORMATION SCIENCES, 1998, 112 (1-4) : 39 - 49
  • [4] Rough Set Approaches for Mining Incomplete Information Systems
    Sabu, M. K.
    Raju, G.
    [J]. ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS, PROCEEDINGS: WITH ASPECTS OF ARTIFICIAL INTELLIGENCE, 2008, 5227 : 914 - +
  • [5] Constrained tolerance rough set in incomplete information systems
    Wan, Renxia
    Miao, Duoqian
    Pedrycz, Witold
    [J]. CAAI TRANSACTIONS ON INTELLIGENCE TECHNOLOGY, 2021, 6 (04) : 440 - 449
  • [6] An approach to rough set decomposition of incomplete information systems
    Qizhong, Zhang
    [J]. ICIEA 2007: 2ND IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS, VOLS 1-4, PROCEEDINGS, 2007, : 2455 - 2460
  • [7] A new extension model of rough sets under incomplete information
    Yin, Xuri
    Jia, Xiuyi
    Shang, Lin
    [J]. ROUGH SETS AND KNOWLEDGE TECHNOLOGY, PROCEEDINGS, 2006, 4062 : 141 - 146
  • [8] Rough set data analysis algorithms for incomplete information systems
    Chin, KS
    Liang, JY
    Dang, CY
    [J]. ROUGH SETS, FUZZY SETS, DATA MINING, AND GRANULAR COMPUTING, 2003, 2639 : 264 - 268
  • [9] A Relative Tolerance Relation of Rough Set for Incomplete Information Systems
    Saedudin, Rd. Rohmat
    Mahdin, Hairulnizam
    Kasim, Shahreen
    Sutoyo, Edi
    Yanto, Iwan Tri Riyadi
    Hassan, Rohayanti
    [J]. RECENT ADVANCES ON SOFT COMPUTING AND DATA MINING (SCDM 2018), 2018, 700 : 72 - 81
  • [10] Knowledge acquisition in incomplete information systems: A rough set approach
    Leung, Y
    Wu, WZ
    Zhang, WX
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2006, 168 (01) : 164 - 180