| Clustering is a fundamental problem that has numerous applications in many disciplines. Clustering techniques are used to discover natural groups in datasets and to identify abstract structures that might reside there, without having any background knowledge of the characteristics of the data. They have been used in various areas including bioinformatics, computer vision, data mining, gene expression analysis, text mining, VLSI design, and Web page clustering to name just a few. Numerous recent contributions to this research area are scattered in a variety of publications in multiple research fields.
This volume collects contributions of computers scientists, data miners, applied mathematicians, and statisticians from academia and industry. It covers a number of important topics and provides about 500 references relevant to current clustering research (we plan to make this reference list available on the Web). We hope the volume will be useful for anyone willing to learn about or contribute to clustering research.
The editors would like to express gratitude to the authors for making their research available for the volume. Without these individuals’ help and cooperation this book would not be possible. Thanks also go to Ralf Gerstner of Springer for his patience and assistance, and for the timely production of this book. We would like to acknowledge the support of the United States–Israel Binational Science Foundation through the grant BSF No. 2002-010, and the support of the Fulbright Program.
This book fills such a gap and meets the demand of many researchers and practitioners who would like to have a solid grasp of the state of the art on cluster analysis methods and their applications. The book consists of a collection of chapters, contributed by a group of authoritative researchers in the field. It covers a broad spectrum of the field, from comprehensive surveys to in-depth treatments of a few important topics. The book is organized in a systematic manner, treating different themes in a balanced way. It is worth reading and further when taken as a good reference book on your shelf.
About the Author
Jacob Kogan is an Associate Professor in the Department of Mathematics and Statistics at the University of Maryland Baltimore County. Dr. Kogan received his Ph.D. in Mathematics from Weizmann Institute of Science, and has held teaching and research positions at the University of Toronto and Purdue University. His research interests include Text and Data Mining, Optimization, Calculus of Variations, Optimal Control Theory, and Robust Stability of Control Systems. From 2001 he has also been affiliated with the Department of Computer Science and Electrical Engineering, University of Maryland Baltimore County. Charles Nicholas is currently a Professor of Computer Science and Chair of the Computer Science and Electrical Engineering Department at UMBC, where he has been since 1988. He received his Ph.D. from The Ohio State University in 1988. Dr. Nicholas' research interestsinclude electronic document processing, information retrieval, and software engineering. Dr. Nicholas has served five times as the General Chair of the ACM Conference on Information and Knowledge Management (CIKM), most recently in 2002. He also twice chaired the Workshop on Digital Document Processing, PODP'96 and PODDP'98. Marc Teboulle is a Professor in the School of Mathematical Sciences, Tel-Aviv University. He received his D.Sc. from the Technion, Israel Institute of Technology in 1985, and has held positions at the Israel Aircraft Industries, Dalhousie University, the University of Maryland, and visiting positions in various academic institutions in France and the USA. His main research interests are in the area of nonlinear optimization: theory , algorithmic analysis and its applications. He is on the editorial board of the journals: Mathematics of Operations Research and the European Series in Applied and Industrial Mathematics, Control, Optimisation and Calculus of Variations. He served as chairman of the Department of Statistics and Operations Research at the School of Mathematical Sciences of Tel-Aviv University during 1999-2002. |
