Publications

*Copyright Notice*
Internal or personal use of these materials is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the corresponding publishers.

• Journal Articles

  Published & Accepted

  1. Shi Zhong. Semi-Supervised Model-based Document Clustering: A Comparative Study. Accepted to Machine Learning. 2005.
  2. Shi Zhong. Efficient Streaming Text Clustering. To appear in Neural Networks. 2005.
  3. Shi Zhong, Taghi M. Khoshgoftaar, and Naeem Seliya. Clustering-based Network Intrusion Detection. To appear in International Journal of Reliability, Quality, and Safety Engineering. 2005.
  4. Shi Zhong. Semi-supervised Sequence Classification with HMMs. International Journal of Pattern Recognition and Artificial Intelligence. vol. 19, no. 2, pp. 165-182. 2005.
  5. Shi Zhong and Joydeep Ghosh. Generative model-based clustering of documents: a comparative study. Knowledge and Information Systems: An International Journal. In Press. February 2005. [The original publication can be found on springerlink.com.]
  6. Taghi M. Khoshgoftaar, Shi Zhong, and Vedang Joshi. Enhancing Software Quality Estimation Using Ensemble-Classifier Filter Based Noise Filtering. Intelligent Data Analysis: An International Journal. vol. 9, no. 1, pp. 3-27. 2005.
  7. Shi Zhong, Taghi M. Khoshgoftaar, and Naeem Seliya. Analyzing software measurement data with clustering techniques. IEEE Intelligent Systems. vol. 19, no. 2, pp. 20-27. March/April 2004. [online magazine version]
  8. Shi Zhong and Joydeep Ghosh. A Unified Framework for Model-based Clustering. Journal of Machine Learning Research. vol. 4, pp. 1001-1037. November, 2003.

  Under Review

  1. Shi Zhong, Taghi M. Khoshgoftaar, and Naeem Seliya. Expert-based Software Quality Estimation with Clustering Techniques. Submission under review. 2004.
  2. Naeem Seliya, Taghi M. Khoshgoftaar, and Shi Zhong. Active Learning with Neural Networks for Intrusion Detection. Submission under review. 2005.

   

• Refereed Conference and Workshop Papers

1. Shi Zhong, Wei Tang, and Taghi M. Khoshgoftaar. Boosted Noise Filters for Identifying Mislabeled Data. Submission under review. 2005
2. Taghi M. Khoshgoftaar, Shyam V. Nath, Shi Zhong, and Naeem Seliya. Wireless network intrusion detection with clustering and expert analysis. Submission under review. 2005.
3. Shi Zhong, Taghi M. Khoshgoftaar, and Shyam V. Nath. A clustering approach to wireless network intrusion detection. Accepted to Proc. IEEE 17th Int. Conf. Tools with Artificial Intelligence (ICTAI-2005). Hongkong. November 2005.
4. Naeem Seliya, Taghi M. Khoshgoftaar, and Shi Zhong. Analyzing Software Quality with Limited Fault-Proneness Defect Data. Accepted to 9th IEEE Int. Symp. High Assurance Systems Engineering (HASE'05), Heidelberg, Germany. October 13-14, 2005.
5. Shi Zhong. Efficient Online Spherical K-means Clustering. In Proc. IEEE Int. Joint Conf. Neural Networks (IJCNN 2005), pp. 3180-3185, Montreal, Canada. July 31-August 4, 2005.
6. Naeem Seliya, Taghi M. Khoshgoftaar, and Shi Zhong. Semi-supervised Learning for Software Quality Estimation. In Proc. IEEE 16th Int. Conf. Tools with Artificial Intelligence (ICTAI-2004), pp. 183-190. November, 2004.
7. David DeMaris, Dan Maynard, Bette B. Reuter, and Shi Zhong. An Information Retrieval System for the Analysis of Systematic Defect in VLSI. In Proc. IEEE 16th Int. Conf. Tools with Artificial Intelligence (ICTAI-2004), pp. 216-223. November, 2004.
8. Shi Zhong, Taghi M. Khoshgoftaar, and Naeem Seliya. Evaluating Clustering Techniques for Network Intrusion Detection. In 10th ISSAT Int. Conf. on Reliability and Quality Design, pp. 149-155. Las Vegas, Nevada, USA. August 2004.
9. Shi Zhong. Semi-Supervised Sequence Classification with HMMs. In 17th International FLAIRS Conference (FLAIRS 2004), pp. 568-573. Miami Beach, FL. May 2004.
10. Shi Zhong. Semi-Supervised Model-based Clustering: A Comparative Study. In SDM Workshop on Clustering High Dimensional Data and Its Applications, pp. 74-85. Orlando, FL. April 2004.
11. Shi Zhong, Taghi M. Khoshgoftaar, and Naeem Seliya. Unsupervised Learning for Expert-based Software Quality Estimation. In 8th IEEE Int. Symp. High Assurance Systems Engineering (HASE'04), pp. 149-155, Tempa, FL. March 2004.
12. Shi Zhong and Joydeep Ghosh. Model-based clustering with soft balancing. In Proc. 3rd IEEE Int. Conf. Data Mining, pp. 459-466, Melbourne, FL. November 2003.
13. Shi Zhong and Joydeep Ghosh. A comparative study of generative models for document clustering. In SDM Workshop on Clustering High Dimensional Data and Its Applicatons, San Francisco, CA. May 2003.
14. Shi Zhong and Joydeep Ghosh. Scalable, balanced model-based clustering. In SIAM Int. Conf. Data Mining, pp. 71-82, San Francisco, CA. May 2003.
15. Shi Zhong and Joydeep Ghosh. A unified framework for model-based clustering.  In Intelligent Engineering Systems Through Artificial Neural Networks (ANNIE), St. Louis, MO. November 2002.
16. Shi Zhong and Joydeep Ghosh. HMMs and coupled HMMs for multi-channel EEG classification. In Proc. IEEE Int. Joint Conf. on Neural Networks, vol. 2, pp. 1154-1159, Honolulu, Hawaii. May 2002.
17. Chen He and Shi Zhong. System-level design and software-based implementation of MPEG-4 video encoder. In The Asilomar Conf. on Signals, Systems and Computers, vol. 2, pp. 1058-1062, Pacific Grove, CA. November 2000.
18. Shi Zhong and Joydeep Ghosh. Decision Boundary Focused Neural Network Classifier. In Intelligent Engineering Systems Through Artificial Neural Networks (ANNIE), ASME Press, St. Louis, MO. November 2000.
19. Shi Zhong and Vladimir Cherkassky. Image denoising using wavelet thresholding and model selection. In Proc. IEEE Int. Conf. on Image processing, vol. 3, pp. 263-265, Vancouver, BC, Canada. November 2000.
20. Shi Zhong and Vladimir Cherkassky. Factors Controlling Generalization Ability of MLP Networks. In Proc. IEEE Int. Joint Conf. on Neural Networks, vol. 1, pp. 625-630, Washington DC. July 1999.

 

• Technical Reports, Unpublished Manuscripts, and Theses
  1. Shi Zhong, Wei Tang, and Taghi M. Khoshgoftaar. Boosted Noise Filters for Identifying Mislabeled Data. Technical Report, June 2005. Florida Atlantic University, Boca Raton, FL, USA.
  2. Naeem Seliya, Taghi M. Khoshgoftaar, and Shi Zhong. Active Learning with Neural Networks for Intrusion Detection. Technical Report, January 2005, Florida Atlantic University, Boca Raton, FL, USA.
  3. Shi Zhong and Joydeep Ghosh. Generative Model-based Document Clustering. Tech. Report, Dept. of Computer Science and Engineering. Florida Atlantic University. June 2004.
  4. Shi Zhong. An Analysis of Model-based Clustering, Competitive Learning, and Information Bottleneck. Tech. Report, Dept. of Computer Science and Engineering, Florida Atlantic University. March 2004.
  5. Shi Zhong. Semi-supervised Model-based Document Clustering: A Comparative Study. Tech. Report, Dept. of Computer Science and Engineering, Florida Atlantic University, January, 2004.
  6. Shi Zhong. Probabilistic Model-based Clustering of Complex Data. PhD Thesis. The University of Texas at Austin. August 2003.
  7. Shi Zhong and Joydeep Ghosh. A unified framework for model-based clustering and its application to clustering sequences. Tech. Report, May, 2002.
  8. Shi Zhong. Probabilistic model-based clustering of time series. Ph.D. qualifying proposal, University of Texas at Austin, May, 2002.
  9. Shi Zhong and Joydeep Ghosh. Coupled Hidden Markov Models. Tech. Report, ECE Dept., University of Texas at Austin, June, 2001.
  10. Shi Zhong and Vladimir Cherkassky. Image denoising using wavelet thresholding and statistical learning theory. submitted to IEEE Trans. Image Processing. 2000.

©Shi Zhong, 2003-2005