NDLI: Mining Association Rules Based on Apriori Algorithm and Application

Content Provider	IEEE Xplore Digital Library
Author	Pei-ji Wang Lin Shi Jin-niu Bai Yu-lin Zhao
Copyright Year	2009
Abstract	In the data mining research, mining association rules is an important topic. Apriori algorithm submitted by Agrawal and R. Srikant in 1994 is the most effective algorithm. Aimed at two problems of discovering frequent itemsets in a large database and mining association rules from frequent itemsets, I make some research on mining frequent itemsets algorithm based on apriori algorithm and mining association rules algorithm based on improved measure system. Mining association rules algorithm based on support, confidence and interestingness is improved, aiming at creating interestingness useless rules and losing useful rules. Useless rules are cancelled, creating more reasonable association rules including negative items. The above method is used to mine association rules to the 2002 student score list of computer specialized field in Inner Mongolia university of science and technology.
Starting Page	141
Ending Page	143
File Size	282231
Page Count	3
File Format	PDF
ISBN	9780769539300
e-ISBN	9781424454235
DOI	10.1109/IFCSTA.2009.41
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-12-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Mathematics Data mining Association rules Application software Recognizable matrix Association rules mining Information systems Itemsets Databases Physics computing Computer applications Biology computing Apriori algorithm Application
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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