Description
Data Mining: Opportunities and Challenges presents an overview of the state of the art approaches in this new and multidisciplinary field of data mining. The primary objective of this book is to explore the myriad issues regarding data mining, specifically focusing on those areas that explore new methodologies or examine case studies. This book contains numerous chapters written by an international team of forty-four experts representing leading scientists and talented young scholars from seven different countries.
Reviews and Testimonials
Data Mining: Opportunities and Challenges offers an up-to-date view on the data mining area by presenting research and development activities and results obtained from the analysis of structured, semi-structured, and unstructured data sources such as text documents, web pages, and databases.
– Domenico Talia, University of Calabria, Italy
This book is a very valuable guide into the field of Data Mining. Addressing theoretical issues and tools from Bayesian Reasoning through Rough Sets to Self-Organizing Maps along with a penetrating look at applications from HealthCare to Banking and Finances, it allows the reader to become acquainted with the state-of-the-art in Data Mining by a group of eminent specialists in this area. It will guide the reader directly to the hearth of the rich world of theory and applications of Data Mining. I am confident that it will become a good companion to any researcher and student in this field.
– Lech Polkowski, Polish-Japanese Institute of Information, Poland
I have read this book with growing interest - this is the first major comprehensive and current introduction to data mining (DM) in ten years. Extremely interesting and useful book! It contains a collection of 20 high quality articles written by experts in data mining (DM) and knowledge discovery (KDD) from the following countries: Argentina, Canada, Finland, Italy, South Africa, Sweden, Taiwan, and USA. The book is filled with fresh insights on data mining: it provides a complete overview of DM-technology and outlines how it can be applied to real world problems and applications.
– Zdzislaw Hippe, University of Information Technology and Management, Poland
This book is a collection of the latest thinking in the area of data mining. The theoretical discussions would be useful to the initiated reader and the cases and experiments are excellent pointers for practitioners.
– Salvator Belardo, University of Albany, USA
Author's/Editor's Biography
John Wang (Ed.)
John Wang is a professor in the Department of Information Management and Business Analytics at Montclair State University, USA. Having received a scholarship award, he came to the USA and completed his PhD in operations research from Temple University. Due to his extraordinary contributions beyond a tenured full professor, Dr. Wang has been honored with two special range adjustments in 2006 and 2009, respectively. He has published over 100 refereed papers and seventeen books. He has also developed several computer software programs based on his research findings. He serves as Editor-in-Chief for ten Scopus-indexed journals, such as Int. J. of Business Analytics, Int. J. of Information Systems and Supply Chain Management, Int. J. of Information Systems in the Service Sector, Int. J. of Applied Management, Int. J. of Information and Decision Sciences, Int. J. of Data Mining, Modelling and Management, etc. He is the Editor of Encyclopedia of Business Analytics and Optimization (five-volume), Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications (six-volume) and the Editor of the Encyclopedia of Data Warehousing and Mining, 1st (two-volume) and 2nd (four-volume). His long-term research goal is on the synergy of operations research, data mining and cybernetics.