TY - GEN
T1 - UP-Miner
AU - Tseng, Vincent Shin-Mu
AU - Wu, Cheng Wei
AU - Lin, Jun Han
AU - Fournier-Viger, Philippe
PY - 2016/1/29
Y1 - 2016/1/29
N2 - 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.
AB - 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.
KW - Cross-platform system
KW - Utility pattern mining
KW - high utility episodes
KW - high utility itemsets
KW - open source toolbox
UR - http://www.scopus.com/inward/record.url?scp=84964720682&partnerID=8YFLogxK
U2 - 10.1109/ICDMW.2015.115
DO - 10.1109/ICDMW.2015.115
M3 - Conference contribution
AN - SCOPUS:84964720682
T3 - Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015
SP - 1656
EP - 1659
BT - Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015
A2 - Wu, Xindong
A2 - Tuzhilin, Alexander
A2 - Xiong, Hui
A2 - Dy, Jennifer G.
A2 - Aggarwal, Charu
A2 - Zhou, Zhi-Hua
A2 - Cui, Peng
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 14 November 2015 through 17 November 2015
ER -