Dr. Shi Zhong

2008

• W. Liu, S. Zhong, M. Chaudhary, and S. Kapur, "Online Advertisement Campaign Optimization," To appear in International Journal of Services Operations and Informatics, 2008
• X. Li, J. Wu, and S. Zhong, "ISRL: Intelligent Search by Reinforcement Learning in Unstructured Peer-to-peer Networks," Parallel Algorithms Appl. 23 (1): 17-44, 2008
  

2007

• W. Liu, S. Zhong, M. Chaudhary, and S. Kapur, "Online Advertisement Campaign Optimization," IEEE SOLI-2007. 
• S. Zhong, T. Khoshgoftaar, and N. Seliya, "Clustering-based network intrusion detection," International Journal of Reliability, Quality and Safety Engineering, Vol. 14, No. 2 (2007) 169-187 
• W. Tang, H. Xiong, S. Zhong, and J. Wu, "Enhancing Semi-Supervised Clustering: A Feature Projection Perspective," KDD 2007.
• Wei Tang and Shi Zhong, "Pairwise Constraints-Guided Dimensionality Reduction," In Computational Methods of Feature Selection, Eds. Huan Liu and Hiroshi Motoda, 2007.

2006

• Wei Tang and Shi Zhong, "Pairwise Constraints-Guided Dimensionality Reduction," Accepted to SDM Workshop on Feature Selection for Data Mining (FSDM'06), Bethesda, Maryland, April, 2006.
• Shi Zhong, "Semi-Supervised Model-based Document Clustering: A Comparative Study," Machine Learning. Vol. 65, No. 1, October 2006.

2005

• Shi Zhong, "Efficient Online Spherical K-means Clustering," In Proc. IEEE Int. Joint Conf. Neural Networks (IJCNN 2005), Montreal, Canada, July 31-August 4, 2005. pp. 3180-3185.
• Shi Zhong, "Efficient Streaming Text Clustering," Neural Networks, Vol. 18, August 2005. pp. 790-798.
• Shi Zhong, "Semi-supervised Sequence Classification with HMMs," International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI), Vol. 19, No. 2, 2005. pp. 165-182.
• Shi Zhong and Joydeep Ghosh, "Generative model-based clustering of documents: a comparative study," Knowledge and Information Systems (KAIS), Vol. 8, 2005. pp. 374-384.

2004

• 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.

2003

• Shi Zhong and Joydeep Ghosh, "A Unified Framework for Model-based Clustering," Journal of Machine Learning Research (JMLR). vol. 4, pp. 1001-1037. November, 2003.
• Shi Zhong and Joydeep Ghosh, "Model-based clustering with soft balancing," In Proc. 3rd IEEE Int. Conf. Data Mining (ICDM 2003), pp. 459-466, Melbourne, FL. November 2003.
• Shi Zhong and Joydeep Ghosh, "Scalable, balanced model-based clustering," In SIAM Int. Conf. Data Mining (SDM 2003), pp. 71-82, San Francisco, CA. May 2003.

2002 and before

• Shi Zhong and Joydeep Ghosh, "HMMs and coupled HMMs for multi-channel EEG classification," In Proc. IEEE Int. Joint Conf. on Neural Networks (IJCNN'02), vol. 2, pp. 1154-1159, Honolulu, Hawaii. May 2002.
• 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.
• 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.
• Shi Zhong and Vladimir Cherkassky, "Image denoising using wavelet thresholding and model selection," In Proc. IEEE Int. Conf. on Image processing (ICIP'00), vol. 3, pp. 263-265, Vancouver, BC, Canada. November 2000.
• Shi Zhong, Yue Yu, Fengting Li, and Chenghui Ge, "Remote Sensing Image Compression Based on Wavelet," Journal of Image and Graphics (in Chinese), vol. 3, no. 10, pp. 849-853, 1998.

Technical Reports

• Shi Zhong, Wei Tang, and Taghi M. Khoshgoftaar, "Boosted Noise Filters for Identifying Mislabeled Data," Technical Report, Dept. of Computer Science and Engineering, Florida Atlantic University, Boca Raton, FL, June 2005.
• Shi Zhong, "An Analysis of Model-based Clustering, Competitive Learning, and Information Bottleneck," Tech. Report, Dept. of Computer Science and Engineering, Florida Atlantic University, Boca Raton, FL, March 2004.
• Shi Zhong, "Probabilistic Model-based Clustering of Complex Data," PhD Thesis, The University of Texas at Austin, August, 2003.
• Shi Zhong and Joydeep Ghosh, "Coupled Hidden Markov Models," Tech. Report, ECE Dept., University of Texas at Austin, June, 2001.

Software Packages
(from Shi Zhong's research)

All programs listed below are distributed under GNU GPL license, thus are free for you to use or distribute. But please be aware that these programs come with absolutely no warranty what so ever, and in no way will I be held responsible for loss of properties due to the use of these software packages.

Model-based Text Clustering (in Matlab)

Brief description: The package contains model-based hard k-means and soft EM clustering algorithms for text applications. Probabilistic models implemented include multivariate Bernoulli, multinomial, and von Mises-Fisher models. Deterministic annealing version of all the above algorithms are also included.

Source code: [textclust.zip] For usage, read the README file.

Text data: [docdata.zip] in Matlab format. For a description of this data, see the reference below.

Reference: Shi Zhong and Joydeep Ghosh, "Generative model-based clustering of documents: a comparative study," Knowledge and Information Systems (KAIS), Vol. 8, 2005. pp. 374-384.

Online Spherical K-Means Clustering (in C & Matlab)

Source code: [C code | Matlab interface | Utility program that can convert text data from Matlab format to CCS format required by the C code.]

Reference: Shi Zhong, "Efficient Online Spherical K-means Clustering," In Proc. IEEE Int. Joint Conf. Neural Networks (IJCNN 2005), Montreal, Canada, July 31-August 4, 2005. pp. 3180-3185.

Coupled Hidden Markov Models (in Matlab)

Source code: [dchmm.zip]

References: Shi Zhong and Joydeep Ghosh, "Coupled Hidden Markov Models," Tech. Report, ECE Dept., University of Texas at Austin, June, 2001.