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Global Business
專任教師 徐銘甫 助理教授





大恩 951

分機 : 

# 36313



中國文化大學 全球商務學位學程助理教授



國立暨南國際大學 國際商業研究系 博士

中國文化大學 會計學 碩士

中國文化大學 會計學 學士




2015年8月-2017年2月  中山大學信息管理系 博士後研究員




  1. T.-M. Chang, Ming-Fu Hsu*, S.-J. Lin (2018), Integrated News Mining Technique and AI-Based Mechanism for Corporate Performance Forecasting. Information Sciences, 424, pp. 273-286. (SCI, IF=4.832)

  2. T.-M. Chang, Ming-Fu Hsu* (2016), Integration of incremental filter-wrapper selection strategy with artificial intelligence for enterprise risk management. International Journal of Machine Learning and Cybernetics– Accepted. DOI : 10.1007/s13042-016-0545-8 (SCI, IF=1.699)

  3. S. J. Lin, Ming-Fu Hsu* (2017), Incorporated risk metrics and hybrid AI techniques for risk management. Neural Computing and Applications 28(11), pp.3477-3489. (SCI, IF=2.505)

  4. P.-F. Pai, Y.-S. Tan, Ming-Fu Hsu (2015),『Credit Rating Analysis by the Decision-Tree Support Vector Machine with Ensemble Strategies』-- International Journal of Fuzzy Systems, Vol. 17, pp 521-530. (IF=1.095, SCI)

  5. S.-J. Lin, Ming-Fu Hsu* (2014), 『Enhanced risk management by an emerging multi-agent architecture』--Connection Science, Vol. 26, pp. 245-259. (IF=0.842, SCI)

  6. J.-J. Liao, C.-H. Shih, T.-F. Chen, Ming-Fu Hsu (2014),『An ensemble-based model for two-class imbalanced financial problem』--Economic Modelling, Vol. 37, pp. 175-183. (IF=0.827, SSCI)

  7. Ming-Fu Hsu, P.-F. Pai (2013),『Incorporating support vector machines with multiple criteria decision making for financial crisis analysis』-- Quality & Quantity, Vol. 47, pp 3481-3492. (IF=0.72, SSCI)

  8. Ming-Fu Hsu, W.-S. Chung, P.-F. Pai (2013),『 A relevance vector machine with rough set theory model in analyzing the life cycle of new economic firms』--Neural Network World. Vol. 23, pp.571-586. (IF=0.479, SCI)

  9. P.-F. Pai, Ming-Fu Hsu, L. Lin (2013), 『Enhancing Decisions with Life Cycle Analysis for Risk Management』-- Neural Computing and Applications, Vol .24, pp 1717-1724. (IF=1.569, SCI)

  10. S.-J. Lin, C.-H. Chang, Ming-Fu Hsu (2013) ,『Multiple extreme learning machines for a two-class imbalance corporate life cycle prediction 』-- Knowledge-Based Systems -- Vol. 39, pp. 214-223. (IF=2.947, SCI)



  1. T. M. Chang, Ming-Fu Hsu*, S. J. Lin, Incorporating Soft Information from Financial News Media for Management Decision in Dynamic Business Environments, 2017 Pre-ICIS Workshop on Accounting Information Systems  (ICIS 2017) (MOST Recommended)
  2. T. M. Chang, Ming-Fu Hsu*, G. H. Hu, K. P. Lin, Integration of Social Media News Mining and Text Mining Techniques to Determine a Corporate’s Competitive Edge, Pacific Asia Conference on Information Systems  (PACIS 2017) (MOST Recommended)
  3. T. M. Chang, Ming-Fu Hsu*, G. H. Hu, K. P. Lin, Salient Corporate Performance Forecasting based on Financial and Textual Information, 2016 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2016) —(MOST Recommended)
  4. T.-M. Chang, C.-H. Sung, G.-H. Hu, Ming-Fu Hsu, K.-P. Lin, 『Identifying Highly Potential Enterprises with Social Computing on Supply Chain Networks』, The 8th IEEE International Conference on Social Computing and Networking (SocialCom 2015)—(MOST Recommended)
  5. J.-H. Wu, S.-S. Shin, T.-M. Chang, A. Gupta, Ming-Fu Hsu, Ex-Ante PLM Misfit Analysis Methodology: A Cognitive Fit Approach, Pacific Asia Conference on Information Systems  (PACIS 2015) (MOST Recommended)