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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Using MapReduce Framework for Mining Association Rules
verfasst von : Shih-Ying Chen, Jia-Hong Li, Ke-Chung Lin, Hung-Ming Chen, Tung-Shou Chen
Erschienen in: Information Technology Convergence
Verlag: 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.