2015 IEEE International Conference on Data Mining Workshop (ICDMW) (2015)
Atlantic City, NJ, USA
Nov. 14, 2015 to Nov. 17, 2015
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.
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
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