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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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File | Description | Size | Format | |
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203-Incremental-Eclat model An implementation via benchmark case study.pdf | Full Text File | 376.08 kB | Adobe PDF | View/Open |
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