SPECIALTY
Research Background: Data mining is an interdisciplinary research area spanning several disciplines such as database systems, machine learning, intelligent information systems, statistics and expert systems. Making economic decisions is a very interesting and prospective domain in data mining, especially in stock market. Rough Sets Theory is a new mathematical approach to imprecision, vagueness and uncertainty in data mining. How to use Rough Sets Theory to extract useful information from economic data is a new research area nowadays.
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Presentations:
Publications:
- Lixiang Shen, Francis E. H. Tay, Liangsheng Qu and Yudi Shen (2000), Fault Diagnosis using Rough Sets Theory
, Computers in Industry, vol. 43, Issue 1, 1 August 2000, pp.61-72.
- Francis E. H. Tay and Lixiang Shen (2000), Contingency Management based on Rough Sets Theory, submitted to Int’l J. of Applied Mathematics and Computer Science.
- Francis E. H. Tay and Lixiang Shen (2000), A Modified Chi2 Algorithm for Discretization, Accepted by IEEE Trans. on Knowledge and Data Engineering.
- Francis E. H. Tay and Lixiang Shen (2000), Economic Prediction using Rough Sets Model, submitted to the European Journal of Operational Research.
- Lixiang Shen and Francis E. H. Tay (2000), Classifying Market States with WARS, in: Wong Sak Leung, Lai-wan Chan and Helen Meng (eds.),
Intelligent Data Engineering and Automated Learning - IDEAL 2000. Data Mining, Financial Engineering, and Intelligent Agents, Second International Conference, Shatin, N.T., Hong Kong, December 13-15, 2000. Proceedings. Lecture Notes in Computer Science.VOL. 1983.pp280-285.
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