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Using unique-prime-factorization theorem to mine frequent patterns without generating tree


Tohidi, Hossein and Ibrahim, Hamidah (2011) Using unique-prime-factorization theorem to mine frequent patterns without generating tree. American Journal of Economics and Business Administration, 3 (1). pp. 58-65. ISSN 1945-5488; ESSN: 1945-5496


Problem statement: Ffrequent patterns are patterns that appear in a data set frequently. Finding such frequent patterns plays an essential role in mining associations, correlations and many other interesting relationships among data. Approach: Most of the previous studies adopt an Apriorilike approach. For huge database it may need to generate a huge number of candidate sets. An interest solution is to design an approach that without generating candidate is able to mine frequent patterns. Results: An interesting method to frequent pattern mining without generating candidate pattern is called frequent-pattern growth, or simply FP-growth, which adopts a divide-and-conquer strategy as follows. However, for a large database, constructing a large tree in the memory is a time consuming task and increase the time of execution. In this study we introduce an algorithm to generate frequent patterns without generating a tree and therefore improve the time complexity and memory complexity as well. Our algorithm works based on prime factorization and is called Prime Factor Miner (PFM). Conclusion/Recommendations: This algorithm is able to achieve low memory order at O(1) which is significantly better than FP-growth.

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Additional Metadata

Item Type: Article
Divisions: Faculty of Computer Science and Information Technology
DOI Number: https://doi.org/10.3844/ajebasp.2011.58.65
Publisher: Science Publications
Keywords: Data mining; Frequent pattern mining; Association rule mining
Depositing User: Nabilah Mustapa
Date Deposited: 10 Jun 2016 08:49
Last Modified: 10 Jun 2016 08:49
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.3844/ajebasp.2011.58.65
URI: http://psasir.upm.edu.my/id/eprint/22476
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