An Efficient Association Rules Mining Algorithm Based on Coding and Constraints

The mining association rules is an important research field in data mining. The traditional association rule mining methods often generate too many candidate items and have to scan whole database for generating each candidate item. An efficient association rules mining scheme has been proposed in th...

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Bibliographic Details
Published in2009 2nd International Conference on Biomedical Engineering and Informatics pp. 1 - 5
Main Authors Zhi Liu, Mingyu Lu, Weiguo Yi, Hao Xu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2009
Subjects
Association rules
Cardiovascular diseases
Costs
Data mining
Educational institutions
Hospitals
Information science
Itemsets
Transaction databases
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ISBN9781424441327
1424441323
ISSN1948-2914
DOI10.1109/BMEI.2009.5304826

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Summary:The mining association rules is an important research field in data mining. The traditional association rule mining methods often generate too many candidate items and have to scan whole database for generating each candidate item. An efficient association rules mining scheme has been proposed in this paper. First, the sub-block coding method is used for the properties. Moreover, the constraints are made for the antecedent and consequent of rules. By using above strategies, the number of candidate items has reduced as well as the scanning size of the database. Therefore, the algorithm greatly improves the operating efficiency. Experimental results demonstrate that the proposed algorithm is more effective than the traditional approach.
ISBN:9781424441327
1424441323
ISSN:1948-2914
DOI:10.1109/BMEI.2009.5304826