Interactive Association Rules Discovery

2006 ◽  
pp. 177-190 ◽  
Author(s):  
Raoul Medina ◽  
Lhouari Nourine ◽  
Olivier Raynaud
Keyword(s):  
Association Rules ◽  
Association Rules Discovery

Mining texts by association rules discovery in a technical corpus

2004 ◽  
pp. 89-98
Author(s):  
Mathieu Roche ◽  
Jérôme Azé ◽  
Oriane Matte-Tailliez ◽  
Yves Kodratoff
Keyword(s):  
Association Rules ◽  
Association Rules Discovery

scholarly journals Design and Implementation of a Generator of Large , Dense ,or Sparse Databases to Test Association Rules Miner

2002 ◽  
Vol 40 (1) ◽  
pp. 25-31
Author(s):  
Hussien Al-Khafaji ◽  
Alaa Al-Hamami ◽  
Abbas F. Abdul-Kader
Keyword(s):  
Data Mining ◽  
Knowledge Discovery ◽  
Association Rules ◽  
Rule Mining ◽  
System Generator ◽  
Qualitative And Quantitative ◽  
Design And Implementation ◽  
Knowledge Discovery In Database ◽  
Mining Algorithms ◽  
Association Rules Discovery

Association rules discovery has emerged as a very important problem in knowledge discovery in database and data mining. A number of algorithms is presented to mine association rules. There are many factors that affect the efficiency of rules mining algorithms, such as largeness, denances, and sparseness of databases used to be mined, in addition to number of items, number and average sizes of transactions, number and average sizes of frequent itemscts, and number and average sizes of potentially maximal itemsets. It is impossible to change present realworld catabase's characteristics to fairly test and determine the best and wurst cases of rule-mining algorithms. to be efficiently used for present and future databases. So the researchers attend to construct artificial database to qualitative and quantitative presence of the above mentioned factors to test the efficiency of rule mining algorithms and programs. The construction of such databases CATmes very large amount of the and efforts. This resent presents a software system, generator, to construct artificial databases.

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