Biography

Tzung-Pei Hong received his B.S. degree in chemical engineering from National Taiwan University, and his Ph.D. degree in computer science and information engineering from National Chiao-Tung University. He is currently a distinguished professor at the Department of Computer Science and Information Engineering and at the Department of Electrical Engineering, National University of Kaohsiung, and a joint professor at the Department of Computer Science and Engineering, National Sun Yat-sen University, Taiwan. He has published more than 400 research papers in international/national journals and conferences and has planned more than fifty information systems.

Area of Interest:

Computer Sciences

100%

Data Mining

62%

Soft Computing

90%

Data Analysis

75%

Internet

55%

Research Publications in Numbers

Books
0

Chapters
0

Articles
0

Abstracts
0

Selected Publications

Vo, B., T. Le, T.P. Hong and B. Le, 2015. Fast updated frequent-itemset lattice for transaction deletion. Data Knowledge Eng., 96: 78-89.
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Tsai, Y.C., S.L. Wang, H.Y. Kao and T.P. Hong, 2015. Edge types vs privacy in K-anonymization of shortest paths. Applied Soft Comput., 31: 348-359.
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Tsai, M.W., T.P. Hong and W.T. Lin, 2015. A two-dimensional genetic algorithm and its application to aircraft scheduling problem. Math. Problems Eng., Vol. 2015. 10.1155/2015/906305.
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Nguyen, D., L.T.T. Nguyen, B. Vo and T.P. Hong, 2015. A novel method for constrained class-association rule mining. Inform. Sci., 320: 107-125.
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Lin, J.C.W., W. Gan, T.P. Hong and J. Zhang, 2015. Updating the built prelarge fast updated sequential pattern trees with sequence modification. Int. J. Data Warehousing Mining, 11: 1-22.
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Lin, J.C.W., W. Gan, T.P. Hong and B. Zhang, 2015. An incremental high-utility mining algorithm with transaction insertion. Sci. World J., 10.1155/2015/161564.
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Lin, J.C.W., W. Gan, P. Fournier-Viger and T.P. Hong, 2015. RWFIM: Recent weighted-frequent itemsets mining. Eng. Applic. Artificial Intell., 45: 18-32.
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Lin, J.C.W., T.P. Hong and T.C. Lin, 2015. A CMFFP-tree algorithm to mine complete multiple fuzzy frequent itemsets. Applied Soft Comput., 28: 431-439.
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Lin, C.W., T.P. Hong, K.T. Yang and S.L. Wang, 2015. The ga-based algorithms for optimizing hiding sensitive itemsets through transaction deletion. Appl. Intell., 42: 210-230.
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Lin, C.W., T.P. Hong and G.C. Lan, 2015. Updating the sequential patterns in dynamic databases for customer sequences deletion. J. Internet Technol., 16: 369-377.
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Lin, C.W., G.C. Lan, T.P. Hong and Y.Y. Wang, 2015. A fast updated high utility pattern trees for transaction deletion. J. Internet Technol., 16: 131-138.
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Lin, C.W., G.C. Lan and T.P. Hong, 2015. Mining high utility itemsets for transaction deletion in a dynamic database. Intell. Data Anal., 19: 43-55.
Lan, G.C., T.P. Hong, Y.H. Lin and S.L. Wang, 2015. Fuzzy utility mining with upper-bound measure. Applied Soft Comput., 30: 767-777.
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Lan, G.C., T.P. Hong, H.Y. Lee and C.W. Lin, 2015. Tightening upper bounds for mining weighted frequent itemsets. Intell. Data Anal., 19: 413-419.
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Kannan, S.R., R. Devi, S. Ramathilagam, T.P. Hong and A. Ravikumar, 2015. Robust fuzzy clustering algorithms in analyzing high-dimensional cancer databases. Applied Soft Comput., 35: 199-213.
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Hong, T.P., C.H. Chen and F.S. Lin, 2015. Using the group genetic algorithm to improve performance of attribute clustering. Applied Soft Comput., 29: 371-378.