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A new and versatile method for association generation

  • Published:1997-09 Issue:6-7 Volume:22 Page:333-347
  • ISSN:0306-4379
  • Container-title:Information Systems
  • language:en
  • Short-container-title:Information Systems

Author:

Amir Amihood,Feldman Ronen,Kashi Reuven

Publisher

Elsevier BV

Subject

Hardware and Architecture,Information Systems,Software

Reference14 articles.

1. Database mining: a performance perspective;Agrawal;IEEE Trans. Knowledge and Data Engineering,1993

2. Mining association rules between sets of items in large databases;Agrawal,1993

3. Fast algorithms for mining association rules in large databases;Agrawal,1994

4. Incremental algorithms for association generation;Feldman,1996

5. Knowledge discovery in textual databases;Feldman,1995

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1. Feature Selection by Principle Component Analysis for Mining Frequent Association Rules;Proceedings of the First International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’16);2016

2. Bit-Table Based Biclustering and Frequent Closed Itemset Mining in High-Dimensional Binary Data;The Scientific World Journal;2014

3. Fast Frequent Pattern Detection Using Prime Numbers;Intelligent Data Engineering and Automated Learning – IDEAL 2014;2014

4. Automated error detection using association rules;Intelligent Data Analysis;2011-08-25

5. A Bounded and Adaptive Memory-Based Approach to Mine Frequent Patterns From Very Large Databases;IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics);2011-02
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