Please use this identifier to cite or link to this item: http://umt-ir.umt.edu.my:8080/handle/123456789/5672
Title: Incremental-Eclat Model
Other Titles: An Implementation via Benchmark Case Study
Authors: Wan Aezwani Bt Wan Abu Bakar
Zailani B. Abdullah
Md. Yazid B. Md Saman
Masita@Masila Bt Abd Jalil
Mustafa B. Man
Tutut Herawan
Abdul Razak Hamdan
Keywords: Association rule mining
Relational database
Mysql
Frequent itemset
Eclat algorithm
Issue Date: 2016
Publisher: Lecture Notes in Electrical Engineering
Abstract: Association Rule Mining (ARM) is one of the most prominent areas in detecting pattern analysis especially for crucial business decision making. With the aims to extract interesting correlations, frequent patterns, association or casual structures among set of items in the transaction databases or other data repositories, the end product of association rule mining is the analysis of pattern that could be a major contributor especially in managerial decision making. Most of previous frequent mining techniques are dealing with horizontal format of their data repositories. However, the current and emerging trend exists where some of the research works are focusing on dealing with vertical data format and the rule mining results are quite promising. One example of vertical rule mining technique is called Eclat which is the abbreviation of Equivalence Class Transformation.
URI: http://hdl.handle.net/123456789/5672
Appears in Collections:Journal Articles

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