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A Comparative Study of FP-growth Variations

Aiman Moyaid, Said and P.D.D., Dominic and Azween, Abdullah (2009) A Comparative Study of FP-growth Variations. [Citation Index Journal]

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Abstract

Finding frequent itemsets in databases is crucial in data mining for purpose of extracting association rules. Many algorithms were developed to find those frequent itemsets. This paper presents a summarization and a comparative study of the available FP-growth algorithm variations produced for mining frequent itemsets showing their capabilities and efficiency in terms of time and memory consumption.

Item Type:Citation Index Journal
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments / MOR / COE:Departments > Computer Information Sciences
ID Code:794
Deposited By: Assoc Prof Dr Azween Abdullah
Deposited On:18 Mar 2010 00:45
Last Modified:19 Jan 2017 08:25

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