Noise-free attribute-oriented induction

被引:0
|
作者
Hu, Hsiao-Wei [1 ,3 ]
Chen, Yen-Liang [2 ,4 ]
Hong, Jia-Yu [2 ,4 ]
机构
[1] Soo Chow Univ, Sch Big Data Management, Taipei, Taiwan
[2] Natl Cent Univ, Dept Informat Management, Chungli, Taiwan
[3] 70 Linshi Rd, Taipei 111, Taiwan
[4] 300 Jhongda Rd, Taoyuan 32001, Taiwan
关键词
Data mining; Attribute-Oriented Induction; Concept Hierarchy; Noise; KNOWLEDGE DISCOVERY;
D O I
10.1016/j.ins.2021.04.002
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Attribute-oriented induction (AOI) was originally developed to facilitate the mining of generalized knowledge in relational databases. Input data for the AOI method comprises a relational table and a concept tree for each attribute. The output is a small relation that contains a number of generalized tuples which summarize the general characteristics of the relational table. Ideally, the generalized tuples shown in the induction table represent the patterns of information that appear in the table. However, if the input data contains a large amount of noise, the generalized tuples may contain too little information to be useful. Existing research into AOI has yet to focus on the elimination of noise. To fill this gap, we developed two noise-free AOI algorithms that filter out noise to enhance the specificity of AOI results. (c) 2021 Elsevier Inc. All rights reserved.
引用
收藏
页码:333 / 349
页数:17
相关论文
共 50 条
  • [1] An appropriate abstraction for an attribute-oriented induction
    Kudoh, Y
    Haraguchi, M
    DISCOVERY SCIENCE, PROCEEDINGS, 1999, 1721 : 43 - 55
  • [2] Attribute-oriented induction using domain generalization graphs
    Hamilton, HJ
    Hilderman, RJ
    Cercone, N
    EIGHTH IEEE INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE, PROCEEDINGS, 1996, : 246 - 253
  • [3] IMPROVEMENT OF ATTRIBUTE-ORIENTED INDUCTION METHOD BASED ON ATTRIBUTE CORRELATION WITH TARGET ATTRIBUTE
    Qu, Ying
    Li, Xiaoyu
    Wang, He
    PROCEEDINGS OF 2014 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS (ICMLC), VOL 2, 2014, : 670 - 674
  • [4] Study of Attribute-Oriented Induction Based on Variance Analysis
    Li Dongping
    PROCEEDINGS OF 2009 CONFERENCE ON COMMUNICATION FACULTY, 2009, : 181 - 184
  • [5] Mining specific and representative information by the attribute-oriented induction method
    Wu, Chia-Chi
    Chen, Yen-Liang
    Yu, Mei-Ru
    EXPERT SYSTEMS, 2021, 38 (03)
  • [6] Knowledge discovery in fuzzy databases using attribute-oriented induction
    Angryk, RA
    Petry, FE
    FOUNDATIONS AND NOVEL APPROACHES IN DATA MINING, 2006, 9 : 169 - +
  • [7] Quantifiable attribute-oriented generalization
    Chen, H.M.
    Wang, L.Z.
    Jisuanji Yanjiu yu Fazhan/Computer Research and Development, 2001, 38 (02):
  • [8] Efficient rule-based attribute-oriented induction for data mining
    Cheung, DW
    Hwang, HY
    Fu, AW
    Han, JW
    JOURNAL OF INTELLIGENT INFORMATION SYSTEMS, 2000, 15 (02) : 175 - 200
  • [9] Efficient Rule-Based Attribute-Oriented Induction for Data Mining
    David W. Cheung
    H.Y. Hwang
    Ada W. Fu
    Jiawei Han
    Journal of Intelligent Information Systems, 2000, 15 : 175 - 200
  • [10] Automated generalization of fuzzy concept hierarchies for attribute-oriented induction purposes
    Dolan, Jacob
    Angryk, Rafal A.
    PROCEEDINGS OF THE IASTED INTERNATIONAL CONFERENCE ON DATABASES AND APPLICATIONS, 2006, : 66 - +