Dr. Richard S. Segall is Professor of Computer & Information Technology at Arkansas State University in Jonesboro, AR. He holds BS and MS in mathematics, MS in operations research and statistics from Rensselaer Polytechnic Institute in Troy, New York, and PhD in operations research form University of Massachusetts at Amherst. He has served on the faculty of Texas Tech University, University of Louisville, University of New Hampshire, University of Massachusetts-Lowell, and West Virginia University. His publications have appeared in journals including International Journal of Information Technology and Decision Making (IJITDM), International Journal of Information and Decision Sciences (IJIDS), Applied Mathematical Modelling, Kybernetes: International Journal of Systems and Cybernetics, and Journal of the Operational Research Society (JORS). He has book chapters in Encyclopedia of Data Warehousing and Mining, Handbook of Computational Intelligence in Manufacturing and Production Management, and Handbook of Research on Text and Web Mining Technologies.

His research interests include data mining, text mining, web mining, database management, and mathematical modeling. His research has been funded by U.S. Air Force, NASA, Arkansas Biosciences Institute (ABI), and Arkansas Science & Technology Authority (ASTA). He is a member of the Editorial Board of the International Journal of Data Mining, Modelling and Management (IJDMMM), The Open Cybernetics and Systemics Journal, and The Open Medical Informatics Journal. He is a member of the Arkansas Center for Plant-Powered Production (P3), recipient of Session Best Paper awards at the 2008, 2009, 2010 and 2011 World Multi-Conference on Systemics, Cybernetics and Informatics (WMSCI) conferences, and served as Local Arrangements Chair of the 2010 MidSouth Computational Biology & Bioinformatics Society (MCBIOS) Conference.

This talk will summarize research of Dr. Segall that pertains to knowledge discovery obtained with the applications of data, text and web mining. Data/Text/Web mining is the informatics methodology and systemics study of finding hidden patterns in large-scale sets of alphanumeric data/text/web respectively.

This presentation will discuss the applications of data mining to the dimensionality of micro-array databases. Micro-arrays are huge collections of spots that contain massive amounts of compressed data. Micro-arrays are used by researchers in life sciences for genetics because DNA contains so much information on a micro-scale. For example, each spot of a micro-array thus could contain a unique DNA sequence. This research has also been extended to include statistical quality control of microarray gene expression data. This presentation will also discuss the applications of text and web mining to linkage discovery of related documents in a repository and the use of semantic rules for identification of similar records. The results of using web mining technologies for customer and marketing surveys are also discussed.