Extracting content from text continues to be an important research problem for information processing and management. Approaches to capture the semantics of text-based document collections may be based on Bayesian models, probability theory, vector space models, statistical models, or even graph theory. As the volume of digitized textual media continues to grow, so does the need for designing robust, scalable indexing and search strategies (software) to meet a variety of user needs. Knowledge extraction or creation from text requires systematic yet reliable processing that can be codified and adapted for changing needs and environments. This book will draw upon experts in both academia and industry to recommend practical approaches to the purification, indexing, and mining of textual information. It will address document identification, clustering and categorizing documents, cleaning text, and visualizing semantic models of text.
Michael W. Berry holds the title of Full Professor and Associate Department Head in the Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville.
Prof. Berry is the co-author of "Templates for the Solution of Linear Systems:
Building Blocks for Iterative Methods" (SIAM, 1994) and "Understanding Search Engines: Mathematical Modeling and Text Retrieval, Second Edition" (Bestseller, SIAM, 2005) and editor of "Computational Information Retrieval" (SIAM, 2001), "Survey of Text Mining: Clustering, Classification, and Retrieval" (Springer-Verlag, 2003, 2007), "Lecture Notes in Data Mining" (Bestseller, World Scientific, 2006), and "Text Mining: Applications and Theory" (Wiley, 2010). He has published well over 100 peer-refereed journal and conference publications.
He has organized numerous workshops on Text Mining and was Conference Co-Chair of the 2003 SIAM Third International Conference on Data Mining (May 1-3) in San Francisco, CA. He was also Program Co-Chair of the 2004 Co-Chair of the 2003 SIAM Fourth International Conference on Data Mining (April 22-24) in Orlando, FL. He is a member of SIAM, ACM, MAA, and the IEEE Computer Society and is on the editorial board of "Computing in Science and Engineering" and "Statistical Analysis and Data Mining".
His research interests include information retrieval, data and text mining,
computational science, bioinformatics, and parallel computing. Prof. Berry's
research has been supported by grants and contracts from organizations such
as the National Science Foundation, National Institutes of Health, and the
National Aeronautics and Space Administration.
