Expert deduction rules in data mining with association rules: a case study

被引:11
|
作者
Rauch, Jan [1 ]
机构
[1] Univ Econ, Dept Informat & Knowledge Engn, Prague, Czech Republic
关键词
Data mining; Association rules; Domain knowledge; Logical calculus of association rules; Deduction rules; Expert deduction rules; GUHA; KNOWLEDGE;
D O I
10.1007/s10115-018-1206-x
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
An approach to dealing with domain knowledge in data mining with association rules is introduced. We deal with association rules with remarkably enhanced syntax. This opens various possibilities for both logical and expert deduction. An expert deduction rule is a logically incorrect deduction rule which is supported by an indisputable fact concerning the application domain. The expert deduction rule is correct according to the given indisputable fact if a suitable assertion related to the given expert deduction rule can be formally proved from this indisputable fact. Examples of expert deduction rules and their applications are presented.
引用
收藏
页码:167 / 195
页数:29
相关论文
共 50 条
  • [41] Mining Class Association Rules on Dataset with Missing Data
    Hoang-Lam Nguyen
    Nguyen, Loan T. T.
    Kozierkiewicz, Adrianna
    INTELLIGENT INFORMATION AND DATABASE SYSTEMS, ACIIDS 2021, 2021, 12672 : 104 - 116
  • [42] Mining association rules from structured xml data
    Faculty of Computer Science, Information Technology, University Putra Malaysia, Serdang, Selangor, 43400, Malaysia
    Proc. Int. Conf. Electr. Eng. Informatics, ICEEI, 1600, (376-379):
  • [43] Mining of association rules in medical image data sets
    Ehikioya, S.A.
    Olukunle, A.
    Journal of Digital Imaging, 2003, 16 (SUPPL.) : 2 - 4
  • [44] Visualizing association rules in a framework for visual data mining
    Buono, P
    Costabile, MF
    FROM INTEGRATED PUBLICATION AND INFORMATION SYSTEMS TO VIRTUAL INFORMATION AND KNOWLEDGE ENVIRONMENTS: ESSAYS DEDICATED TO ERICH J NEUHOLD ON THE OCCASION OF HIS 65TH BIRTHDAY, 2005, 3379 : 221 - 231
  • [45] Mining Association Rules for RFID Data with Concept Hierarchy
    Kim, Younghee
    Kim, Ungmo
    Jung, Myungsook
    Kang, Woojun
    Noh, Youngju
    11TH INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION TECHNOLOGY, VOLS I-III, PROCEEDINGS,: UBIQUITOUS ICT CONVERGENCE MAKES LIFE BETTER!, 2009, : 1002 - +
  • [46] Mining spatial gene expression data for association rules
    van Hemert, Jano
    Baldock, Richard
    BIOINFORMATICS RESEARCH AND DEVELOPMENT, PROCEEDINGS, 2007, 4414 : 66 - +
  • [47] On association rules mining algorithms with data privacy preserving
    Gorawski, M
    Stachurski, K
    ADVANCES IN WEB INTELLIGENCE, PROCEEDINGS, 2005, 3528 : 170 - 175
  • [48] Mining association rules in preference-ordered data
    Greco, S
    Slowinski, R
    Stefanowski, J
    FOUNDATIONS OF INTELLIGENT SYSTEMS, PROCEEDINGS, 2002, 2366 : 442 - 450
  • [49] Effect of data skewness in parallel mining of association rules
    Cheung, DW
    Xiao, YQ
    RESEARCH AND DEVELOPMENT IN KNOWLEDGE DISCOVERY AND DATA MINING, 1998, 1394 : 48 - 60
  • [50] Approach of organization data based on mining of association rules
    Kong, Lingfu
    Wang, Han
    Lian, Qiusheng
    Jisuanji Gongcheng/Computer Engineering, 2006, 32 (21): : 12 - 14