Michael W. Berry

Professor - Electrical Engineering and Computer Science Department

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Dr. Michael W. Berry holds the title of Full Professor in the Department of Electrical Engineering and Computer Science and Director of the Center for Intelligent Systems and Machine Learning (CISML) in the College of Engineering.  He received the BS degree in Mathematics from the University of Georgia in 1981 and the MS degree in Applied Mathematics from North Carolina State University in 1983.  In 1990, he received the PhD degree in Computer Science from the University of Illinois at Urbana-Champaign.  Dr. Berry was the recipient of the Moses E. and Mayme Brooks Distinguished Professor Award (UTK College of Engineering) in 2009, the Allen Hoshall Engineering Faculty Award (UTK College of Engineering) in 2010, the L.R. Hesler Award for Excellence in Teaching in Service (UTK Chancellor’s Honors) in 2011, and the Charles Edward Ferris Faculty Award (UTK College of Engineering) in 2011.  His research interests include information retrieval, text/data mining, computational science, bioinformatics, and scientific computing.

Focus Areas:  Machine Learning | Knowledge Discovery | Bioinformatics | Information Retrieval | Scientific Computing

Skills and Expertise: Text/Data Mining | Social Media Mining | Nonnegative Matrix and Tensor Factorization | Numerical Linear Algebra

Selected Publications:

The Use of Text Mining Techniques in Electronic Discovery for Legal Matters'
M.W. Berry, R. Esau, and B. Kiefer, Next Generation Search Engines: Advanced Models for Information Retrieval, C. Jouis and I. Biskri (Eds.), IGI Global, pp. 174-190, 2012.
Latent Semantic Indexing of Pubmed Abstracts for Identification of Transcription Factor Candidates from Microarray-derived Gene Sets
S. Roy, K. Heinrich, V. Phan, M.W. Berry, and R. Homayouni, BMC Bioinformatics, vol. 12, suppl. 10, pp. S19, 2011.
Nonnegative Matrix and Tensor Factorization for Discussion Tracking
B.W. Bader, M.W. Berry, and A.N. Langville, Text Mining: Classification, Clustering, and Applications, A. Srivastava and M. Sahami (Eds.), Chapman & Hall/CRC Press, pp. 95-120, 2009.
Nonnegative Matrix Factorization for Anomaly and Trend Detection
A.N. Langville and M.W. Berry, Next Generation of Data Mining, H. Kargupta, J. Han, P. Yu, R. Motwani, and V. Kumar (Eds.), CRC Press, pp. 335-352, 2008.
Algorithms and Applications for Approximate Nonnegative Matrix Factorization
M.W. Berry, M. Browne, A.N. Langville, V.P. Pauca, and R.J. Plemmons, Computational Statistics & Data Analysis , vol. 52, no. 1, pp. 155-178, 2007.
Mathematical Foundations Behind Latent Semantic Analysis
D.I. Martin and M.W. Berry, Handbook of Latent Semantic Analysis, T.K. Landauer, D.S. McNamara, S. Dennis, and W. Kintsch (Eds), Lawrence Erlbaum Associates, pp. 35-55, 2007.
Document Clustering Using Nonnegative Matrix Factorization
F. Shahnaz, M.W. Berry, V.P. Pauca, and R.J. Plemmons, Information Processing & Management, vol. 42, no. 2, pp. 373-386, 2006.
Computing Sparse Reduced-Rank Approximations to Sparse Matrices
M.W. Berry, S.A. Pulatova, and G.W. Stewart, ACM Transactions on Mathematical Software, vol. 31, no. 2, pp. 353-269, 2005.
Gene Clustering by Latent Semantic Indexing of MEDLINE Abstracts
R. Homayouni, K. Heinrich, L. Wei, and M.W. Berry, Bioinformatics, vol. 21, no. 1, pp. 104-115, 2005.
GTP (General Text Parser) Software for Text Mining
J.T. Giles, L. Wo, and M.W. Berry, Stat. Data Mining and Know. Discovery, H. Bozdogan (Ed.), CRC Press, Boca Raton, pp. 455-471, 2003.