DocumentCode
3423803
Title
Mining opened frequent itemsets to generate maximal Boolean association rules
Author
Jiang, Baoqing ; Han, Chong ; Li, Lingsheng
Author_Institution
Inst. of Data & Knowledge Eng., Henan Univ., Kaifeng, China
fYear
2009
fDate
17-19 Aug. 2009
Firstpage
274
Lastpage
277
Abstract
Lots of association rules may be generated in the process of association rules minging. It leads to users hard to find important information they needed. The maximal Boolean association rules have the advantages that these rules contain a small number and don´t lose the rules´ information. Thereby it increased the efficiency of the users´ analysis about the rules and saved the storage space. Opened frequent itemsets and closed frequent itemsets can be used to mine the maximal Boolean association rules. In this paper, we analyse the property of maximal Boolean association rules and propose an algorithm of mining opened frequent itemset. Finally, we verify this algorithm by an example.
Keywords
Boolean functions; data mining; closed frequent itemsets; maximal boolean association rules; opened frequent itemsets mining; Algorithm design and analysis; Association rules; Data mining; Diseases; Explosions; Itemsets; Knowledge engineering; Transaction databases;
fLanguage
English
Publisher
ieee
Conference_Titel
Granular Computing, 2009, GRC '09. IEEE International Conference on
Conference_Location
Nanchang
Print_ISBN
978-1-4244-4830-2
Type
conf
DOI
10.1109/GRC.2009.5255112
Filename
5255112
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