Dr. Flora S. Tsai
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Dr. Flora S. Tsai

Lecturer
Nanyang Technology University, Singapore


Highest Degree
Ph.D. in Electrical and Electronic Engineering from Nanyang Technology University, Singapore

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Area of Interest:

Computer Sciences
100%
Data Mining
62%
Information Retrieval
90%
Software Engineering
75%
Text Mining
55%

Research Publications in Numbers

Books
0
Chapters
6
Articles
36
Abstracts
18

Selected Publications

  1. Zhang, Y., F.S. Tsai and A.T. Kwee, 2011. Multilingual sentence categorization and novelty mining. Inf. Process. Manage., 47: 667-675.
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  2. Tsai, F.S., Y. Zhang, A.T. Kwee and W. Tang, 2011. Multilingual novelty detection. Expert Syst. Appl., 38: 652-658.
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  3. Tsai, F.S., 2011. Web-based geographic search engine for location-aware search in Singapore. Expert Syst. Appl., 38: 1011-1016.
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  4. Tsai, F.S., 2011. Dimensionality reduction techniques for blog visualization. Expert Syst. Appl., 38: 2766-2773.
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  5. Tsai, F.S., 2011. A tag-topic model for blog mining. Expert Syst. Appl., 38: 5330-5335.
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  6. Tsai, F.S. and K.L. Chan, 2011. An intelligent system for sentence retrieval and novelty mining. Int. J. Knowl. Eng. Data Min., 1: 235-253.
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  7. Tsai, F.S., W. Tang and K.L. Chan, 2010. Evaluation of novelty metrics for sentence-level novelty mining. Inform. Sci., 180: 2359-2374.
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  8. Tsai, F.S., M. Etoh, X. Xie, W.C. Lee and Q. Yang, 2010. Introduction to mobile information retrieval. IEEE Intell. Syst., 25: 11-15.
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  9. Tsai, F.S., A.T. Kwee, W. Tang and K.L. Chan, 2010. Adaptable services for novelty mining. Int. J. Syst. Service-Oriented Eng., 1: 69-85.
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  10. Tsai, F.S., 2010. Security issues in E-healthcare. J. Med. Biol. Eng., 30: 209-214.
  11. Tsai, F.S., 2010. Review of techniques for intelligent novelty mining. Inform. Technol. J., 9: 1255-1261.
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  12. Tsai, F.S., 2010. Comparative study of dimensionality reduction techniques for data visualization. J. Artificial Intell., 3: 119-134.
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  13. Tsai, F.S. and K.L. Chan, 2010. Redundancy and novelty mining in the business blogosphere. The Learn. Organ., 17: 490-499.
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  14. Tang, W., F.S. Tsai and L. Chen, 2010. Blended metrics for novel sentence mining. Expert Syst. Appl., 37: 5172-5177.
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  15. Tan, R.H.R. and F.S. Tsai, 2010. Authorship identification for online text. Proceedings of the International Conference on Cyberworlds, Oct. 20-22, Singapore, pp: 155-162.
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  16. Chan, C.S. and F.S. Tsai, 2010. Computer animation of facial emotions. Proceedings of the International Conference on Cyberworlds, Oct. 20-22, Singapore, pp: 425-429.
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  17. Zhang, Y. and F.S. Tsai, 2009. Combining named entities and tags for novel sentence detection. Proceedings of the WSDM'09 Workshop on Exploiting Semantic Annotations in Information Retrieval, Barcelona, Spain, Feb. 09, ACM, New York, USA., pp: 30-34.
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  18. Zhang, Y. and F.S. Tsai, 2009. Chinese novelty mining. Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, Singapore, Aug. 06-07, Association for Computational Linguistics Morristown, New Jersey, USA., pp: 1561-1570.
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  19. Yee, K.Y., A.W. Tiong, F.S. Tsai and R. Kanagasabai, 2009. OntoMobiLe: A generic ontology-centric service-oriented architecture for mobile learning. Proceedings of the 10th International Conference on Mobile Data Management (MDM) Workshop on Mobile Media Retrieval (MMR), May 18-20, Taiwan, pp: 631-636.
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  20. Tsai, F.S., W. Han, J. Xu and H.C. Chua, 2009. Design and development of a mobile peer-to-peer social networking application. Expert Syst. Appl., 36: 11077-11087.
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  21. Tsai, F.S., 2009. Network intrusion detection using association rules. Int. J. Recent Trends Eng., 2: 202-204.
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  22. Tang, W. and F.S. Tsai, 2009. Threshold setting and performance monitoring for novel text mining. Proceedings in Applied Mathematics 3 Society for Industrial and Applied Mathematics-9th SIAM International Conference on Data Mining, Jan. 04-06, New York, pp: 1310-1319.
  23. Ong, C.L., A.T. Kwee and F.S. Tsai, 2009. Database optimization for novelty detection. Proceedings of the 7th International Conference on Information, Communications and Signal Processing, Dec. 8-10, Macau, pp: 1-5.
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  24. Liang, H., F.S. Tsai and A.T. Kwee, 2009. Detecting novel business blogs. Proceedings of the 7th International Conference on Information, Communications and Signal Processing, Dec. 8-10, Macau, pp: 1-5.
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  25. Kwee, A.T., F.S. Tsai and W. Tang, 2009. Sentence-Level Novelty Detection in English and Malay. In: Advances in Knowledge Discovery and Data Mining, Theeramunkong, T. et al. (Eds.). LNCS. 5476, Springer-Verlag, Berlin, Heidelberg, pp: 40-51.
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  26. Kwee, A.T. and F.S. Tsai, 2009. Mobile novelty mining. Int. J. Adv. Pervasive Ubiquitous Comput., 1: 43-68.
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  27. Chen, T., K. Wu, K.H. Yap, Z. Li and F.S. Tsai, 2009. A survey on mobile landmark recognition for information retrieval. Proceedings of IEEE International Conference on Mobile Data Management, May 18-20, Taipei, pp: 625-630.
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  28. Chen, Y., F.S. Tsai and K.L. Chan, 2008. Machine learning techniques for business blog search and mining. Expert Syst. Appl., 35: 581-590.
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  29. Tsai, F.S., Y. Chen and K.L. Chan, 2007. Probabilistic techniques for corporate blog mining. Lecture Notes Artif. Intell., 4819: 35-44.
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  30. Tsai, F.S. and K.L. Chan, 2007. Dimensionality reduction techniques for data exploration. Proceedings of the 6th International Conference on Information, Communications and Signal Processing, Dec. 10-13, Nanyang Technol. Univ., Singapore, pp: 1-5.
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  31. Tsai, F.S. and K.L. Chan, 2007. Detecting Cyber Security Threats in Weblogs Using Probabilistic Models. In: Intelligence and Security Informatics, Yang, C.C. et al. (Eds.). LNCS., 4430. Springer, Berlin, Heidelberg, ISBN: 978-3-540-71548-1, pp: 46-57.
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  32. Ng, K.W., F.S. Tsai, L. Chen and K.C. Goh, 2007. Novelty detection for text documents using named entity recognition. Proceedings of the 6th International Conference on Information, Communications and Signal Processing, Dec. 10-13, Singapore, pp: 1-5.
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  33. Chen, Y., F.S. Tsai and K.L. Chan, 2007. Blog search and mining in the business domain. Proceedings of the International Workshop on Domain Driven Data Mining, San Jose, California, Aug. 12, ACM, New York, USA., pp: 55-60.
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