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2015 IEEE International Conference on Data Mining Workshop (ICDMW) (2015)
Atlantic City, NJ, USA
Nov. 14, 2015 to Nov. 17, 2015
ISSN: 2375-9259
ISBN: 978-1-4673-8492-6
pp: 1656-1659
ABSTRACT
Utility pattern mining has received extensive attentions in recent years due to the wide and novel applications in various fields like e-commerce, Web mining, finance, biomedicine, etc. However, there exists not yet a toolbox for utility pattern mining so far. In this work, we address this issue by proposing a first-of-its-kind toolbox named UP-Miner (Utility Pattern Miner) that provides various functions for utility pattern mining. The main merits of UP-Miner lie in three aspects: First, it offers implementations of thirteen state-of-the-art algorithms for efficiently mining different types of utility patterns, such as high utility itemsets, high utility episodes and utility-based sequential patterns, as well as four functionalities for processing utility-based databases. Second, it is a cross-platform system implemented in Java with a user-friendly graphical interface. Third, the toolbox and relevant materials, including source codes, benchmark datasets and data generators, are made public on Web (http://bigdatalab.cs.nctu.edu.tw/software.htm) for benefiting the research community.
INDEX TERMS
Data mining, Data visualization, Itemsets, Algorithm design and analysis, Dairy products, Diamonds,cross-platform system, Utility pattern mining, high utility itemsets, high utility episodes, open source toolbox
CITATION
Vincent S. Tseng, Cheng-Wei Wu, Jun-Han Lin, Philippe Fournier-Viger, "UP-Miner: A Utility Pattern Mining Toolbox", 2015 IEEE International Conference on Data Mining Workshop (ICDMW), vol. 00, no. , pp. 1656-1659, 2015, doi:10.1109/ICDMW.2015.115
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