Mining Indirect Positive and Negative Association Rules

被引:0
|
作者
Ramasubbareddy, B. [1 ]
Govardhan, A. [2 ]
Ramamohanreddy, A. [3 ]
机构
[1] Jyothishmathi Inst Technol & Sci, Karimnagar, India
[2] JNTUH Coll Engn, Karimnagar, India
[3] SV Univ, SVU Coll Engn, Tirupati, Andhra Pradesh, India
关键词
Data mining; positive and negative association rules; indirect association;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Indirect association is a new kind of infrequent pattern, which provides a new way for interpreting the value of infrequent patterns and can effectively reduce the number of uninteresting infrequent patterns. The concept of indirect association is to "indirectly" connect two rarely co-occurred items via a frequent itemset called mediator, and if appropriately utilized it can help to identify real interesting "infrequent itempairs" from databases. Indirect association rule is said to be positive (Negative) if mediator set contains presence (presence or absence) of items. Existing indirect association mining methods mine positive mediator sets. To the best of our knowledge, no research work has been conducted on mining indirect negative associations. In this paper, we propose an approach for mining indirect negative associations. The proposed method can discover all positive and negative indirect association between itemsets.
引用
收藏
页码:581 / +
页数:3
相关论文
共 50 条
  • [1] MINING POSITIVE AND NEGATIVE ASSOCIATION RULES
    Zhu, Honglei
    Xu, Zhigang
    [J]. PROCEEDINGS OF THE 38TH INTERNATIONAL CONFERENCE ON COMPUTERS AND INDUSTRIAL ENGINEERING, VOLS 1-3, 2008, : 2748 - 2752
  • [2] Mining positive and negative fuzzy association rules
    Yan, P
    Chen, GQ
    Cornelis, C
    De Cock, M
    Kerre, E
    [J]. KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, PT 1, PROCEEDINGS, 2004, 3213 : 270 - 276
  • [3] Mining positive and negative association rules:: An approach for confined rules
    Antonie, ML
    Zaïane, OR
    [J]. KNOWLEDGE DISCOVERY IN DATABASES: PKDD 2004, PROCEEDINGS, 2004, 3202 : 27 - 38
  • [4] Mining Positive and Negative Association Rules with Weighted Items
    Jiang, He
    Zhao, Yuanyuan
    Dong, Xiangjun
    Shang, Shiju
    [J]. DCABES 2008 PROCEEDINGS, VOLS I AND II, 2008, : 437 - 441
  • [5] Efficient mining of both positive and negative association rules
    Wu, XD
    Zhang, CQ
    Zhang, SC
    [J]. ACM TRANSACTIONS ON INFORMATION SYSTEMS, 2004, 22 (03) : 381 - 405
  • [6] An Algorithm for Mining Multidimensional Positive and Negative Association Rules
    Jiang, He
    Bai, Ze
    Liu, Guoling
    Luan, Xiumei
    [J]. ACHIEVEMENTS IN ENGINEERING MATERIALS, ENERGY, MANAGEMENT AND CONTROL BASED ON INFORMATION TECHNOLOGY, PTS 1 AND 2, 2011, 171-172 : 445 - +
  • [7] Research on Mining Sequential Positive and Negative Association Rules
    Jiang, He
    Geng, Runian
    Sun, Baoyou
    [J]. ICICTA: 2009 SECOND INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION TECHNOLOGY AND AUTOMATION, VOL III, PROCEEDINGS, 2009, : 703 - 706
  • [8] Optimized Mining of Potential Positive and Negative Association Rules
    Bemarisika, Parfait
    Totohasina, Andre
    [J]. BIG DATA ANALYTICS AND KNOWLEDGE DISCOVERY, DAWAK 2017, 2017, 10440 : 424 - 432
  • [9] Mining indirect association rules
    Hamano, S
    Sato, M
    [J]. ADVANCES IN DATA MINING: APPLICATIONS IN IMAGE MINING, MEDICINE AND BIOTECHNOLOGY, MANAGEMENT AND ENVIRONMENTAL CONTROL, AND TELECOMMUNICATIONS, 2004, 3275 : 106 - 116
  • [10] RESEARCH AND APPLICATION OF ALGORITHM FOR MINING POSITIVE AND NEGATIVE ASSOCIATION RULES
    Peng, Xushan
    Wu, Yanyan
    [J]. INTERNATIONAL SYMPOSIUM ON COMPUTER SCIENCE & TECHNOLOGY, PROCEEDINGS, 2009, : 438 - 440