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2013 | OriginalPaper | Chapter

Using MapReduce Framework for Mining Association Rules

Authors : Shih-Ying Chen, Jia-Hong Li, Ke-Chung Lin, Hung-Ming Chen, Tung-Shou Chen

Published in: Information Technology Convergence

Publisher: Springer Netherlands

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Abstract

Data mining in knowledge discovery helps people discover unknown patterns from the collected data. PIETM (Principle of Inclusion–Exclusion and Transaction Mapping) algorithmis a novel frequent item sets mining algorithm, which scans database twice. To cope with big transaction database in the cloud, this paper proposes a method that parallelizes PIETM by the MapReduce framework. The method has three modules. Module I counts the supports of frequent 1-item sets. Module II constructs transaction interval lists. Module III discovers all the frequent item sets iteratively.

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Metadata
Title
Using MapReduce Framework for Mining Association Rules
Authors
Shih-Ying Chen
Jia-Hong Li
Ke-Chung Lin
Hung-Ming Chen
Tung-Shou Chen
Copyright Year
2013
Publisher
Springer Netherlands
DOI
https://doi.org/10.1007/978-94-007-6996-0_76