Finding Association Rules through Efficient Knowledge Management Technique

被引:1
作者
Anwar, M. A. [1 ]
机构
[1] Al Ghurair Univ, Coll Engn & Comp, Dubai Acad City, U Arab Emirates
关键词
Data Mining; Co-occurrences; Incremental association rules; Dynamic Databases;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
One of the recent research topics in databases is Data Mining, to find, extract and mine the useful information from databases. In case of updating transactions in the database the already discovered knowledge may become invalid. So we need efficient knowledge management techniques for finding the updated knowledge from the database. There have been lot of research in data mining, but Knowledge Management in databases is not studied much. One of the data mining techniques is to find association rules from databases. But most of association rule algorithms find association rules from transactional databases. Our research is a further step of the Tree Based Association Rule Mining (TBAR) algorithm, used in relational databases for finding the association rules. In our approach of updating the already discovered knowledge; the proposed algorithm Association Rule Update (ARU), updates the already discovered association rules found through the TBAR algorithm. Our algorithm will be able to find incremental association rules from relational databases and efficiently manage the previously found knowledge.
引用
收藏
页码:131 / 134
页数:4
相关论文
共 50 条
  • [41] Data Mining Technique for Reduction of Association Rules in Distributed System
    Waghamare, Bhagyashri
    Bodhe, Yogesh
    2016 INTERNATIONAL CONFERENCE ON AUTOMATIC CONTROL AND DYNAMIC OPTIMIZATION TECHNIQUES (ICACDOT), 2016, : 415 - 418
  • [42] Optimization of association rules using hybrid data mining technique
    Sahana P. Shankar
    E. Naresh
    Harshit Agrawal
    Innovations in Systems and Software Engineering, 2022, 18 : 251 - 261
  • [43] A fast algorithm of mining association rules in network management
    Liu, PQ
    Li, ZZ
    Chen, YX
    Zhao, YL
    2002 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-4, PROCEEDINGS, 2002, : 915 - 918
  • [44] Algorithm of mining fuzzy association rules in network management
    Liu, PQ
    Li, ZZ
    Zhao, YL
    2003 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-5, PROCEEDINGS, 2003, : 123 - 127
  • [45] An efficient algorithm for mining quantitative association rules in large databases
    Lee, HJ
    Park, WH
    Song, SJ
    Park, DS
    IKE'03: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INFORMATION AND KNOWLEDGE ENGINEERING, VOLS 1 AND 2, 2003, : 571 - 576
  • [46] Elimination of Redundant Association Rules-An Efficient Linear Approach
    Jeyapal, Akilandeswari
    Ganesan, Jothi
    COMPUTATIONAL INTELLIGENCE, CYBER SECURITY AND COMPUTATIONAL MODELS, ICC3 2015, 2016, 412 : 171 - 180
  • [47] Application of association rules for efficient learning work-flow
    Encheva, Sylvia
    Tumin, Sharil
    INTELLIGENT INFORMATION PROCESSING III, 2006, 228 : 499 - +
  • [48] Applying association rules to designing an efficient image retrieval model
    Huang, YP
    Chang, TW
    Proceedings of the 8th Joint Conference on Information Sciences, Vols 1-3, 2005, : 1449 - 1452
  • [49] A Novel Efficient Mining Association Rules Algorithm for Distributed Databases
    Shen, Liangzhong
    PROGRESS IN MEASUREMENT AND TESTING, PTS 1 AND 2, 2010, 108-111 : 50 - 56
  • [50] Efficient mining of association rules using closed itemset lattices
    Pasquier, N
    Bastide, Y
    Taouil, R
    Lakhal, L
    INFORMATION SYSTEMS, 1999, 24 (01) : 25 - 46