Tzung-Pei Hong

发表

A fast algorithm for mining high average-utility itemsets

Philippe Fournier-Viger, Chun-Wei Lin, Shifeng Ren, 2017, Applied Intelligence.

Efficient mining of short periodic high-utility itemsets

Philippe Fournier-Viger, Chun-Wei Lin, Tzung-Pei Hong, 2016, 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Efficient Mining of Weighted Frequent Itemsets in Uncertain Databases

Philippe Fournier-Viger, Chun-Wei Lin, Wensheng Gan, 2016, MLDM.

An Efficient Anonymous System for Transaction Data

Justin Zhijun Zhan, Philippe Fournier-Viger, Chun-Wei Lin, 2016, MISNC.

A Swarm-Based Approach to Mine High-Utility Itemsets

Lu Yang, Jimmy Ming-Tai Wu, Philippe Fournier-Viger, 2015, MISNC.

Efficiently mining of skyline frequent-utility patterns

Lu Yang, Philippe Fournier-Viger, Chun-Wei Lin, 2017, Intell. Data Anal..

Effective Quality-Aware Sensor Data Management

Giuseppe D’Aniello, Matteo Gaeta, Tzung-Pei Hong, 2018, IEEE Transactions on Emerging Topics in Computational Intelligence.

A Swarm-Based Sanitization Approach for Hiding Confidential Itemsets

Philippe Fournier-Viger, Chun-Wei Lin, Qiankun Liu, 2015, 2015 International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP).

A Sanitization Approach of Privacy Preserving Utility Mining

Philippe Fournier-Viger, Chun-Wei Lin, Jeng-Shyang Pan, 2015, ICGEC.

Mining high-utility itemsets with various discount strategies

Vincent S. Tseng, Philippe Fournier-Viger, Chun-Wei Lin, 2015, DSAA.

A binary PSO approach to mine high-utility itemsets

Lu Yang, Philippe Fournier-Viger, Chun-Wei Lin, 2017, Soft Comput..

Mining Weighted Frequent Itemsets with the Recency Constraint

Philippe Fournier-Viger, Chun-Wei Lin, Wensheng Gan, 2015, APWeb.

Mining high-utility itemsets based on particle swarm optimization

Lu Yang, Justin Zhijun Zhan, Jimmy Ming-Tai Wu, 2016, Eng. Appl. Artif. Intell..

A survey of incremental high‐utility itemset mining

Hamido Fujita, Philippe Fournier-Viger, Chun-Wei Lin, 2018, WIREs Data Mining Knowl. Discov..

EHAUPM: Efficient High Average-Utility Pattern Mining With Tighter Upper Bounds

Jerry Chun-Wei Lin, Philippe Fournier-Viger, Shifeng Ren, 2017, IEEE Access.

A weighted N-list-based method for mining frequent weighted itemsets

Tu-Anh Nguyen-Hoang, Tzung-Pei Hong, Bay Vo, 2018, Expert Syst. Appl..

Efficient hiding of confidential high-utility itemsets with minimal side effects

Justin Zhijun Zhan, Philippe Fournier-Viger, Chun-Wei Lin, 2017, J. Exp. Theor. Artif. Intell..

Mining Fuzzy Concept-drift Patterns from Quantitative Database Change

Tzung-Pei Hong, Wu Min-Thai, Chen Chun-Hao, 2015 .

Updating the Discovered High Average-Utility Patterns with Transaction Insertion

Philippe Fournier-Viger, Chun-Wei Lin, Tzung-Pei Hong, 2017, ICGEC.

Fast algorithms for mining multiple fuzzy frequent itemsets

Philippe Fournier-Viger, Chun-Wei Lin, Ting Li, 2016, 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

Mining of skyline patterns by considering both frequent and utility constraints

Lu Yang, Philippe Fournier-Viger, Chun-Wei Lin, 2019, Eng. Appl. Artif. Intell..

Efficiently Updating the Discovered Sequential Patterns for Sequence Modification

Philippe Fournier-Viger, Chun-Wei Lin, Wensheng Gan, 2016, Int. J. Softw. Eng. Knowl. Eng..

Efficient Mining of Uncertain Data for High-Utility Itemsets

Vincent S. Tseng, Philippe Fournier-Viger, Chun-Wei Lin, 2016, WAIM.

Mining Discriminative High Utility Patterns

Philippe Fournier-Viger, Chun-Wei Lin, Wensheng Gan, 2016, ACIIDS.

Efficiently updating the discovered high average-utility itemsets with transaction insertion

Philippe Fournier-Viger, Chun-Wei Lin, Jeng-Shyang Pan, 2018, Eng. Appl. Artif. Intell..

Efficient algorithms for mining recent weighted frequent itemsets in temporal transactional databases

Philippe Fournier-Viger, Chun-Wei Lin, Wensheng Gan, 2016, SAC.

Efficiently mining frequent itemsets with weight and recency constraints

Philippe Fournier-Viger, Chun-Wei Lin, Wensheng Gan, 2017, Applied Intelligence.