Product Description
An overview of the multidisciplinary field of data mining, this book focuses specifically on new methodologies and case studies. Included are case studies written by 44 leading scientists and talented young scholars from seven different countries. Topics covered include data mining based on rough sets, the impact of missing data, and mining free text for structure. In addition, the four basic mining operations supported by numerous mining techniques are addressed: predictive model creation supported by supervised induction techniques; link analysis supported by association discovery and sequence discovery techniques; DB segmentation supported by clustering techniques; and deviation detection supported by statistical techniques.
About The Author John Wang is a professor in the department of information and decision sciences at Montclair State University, has a Ph.D. in operations research from Temple University, and has worked as an assistant professor at Beijing University of Sciences and Technology. He has served as a referee for Operations Research and IEEE Transactions on Control Systems Technology. His current research interests include optimization, nonlinear programming, and manufacturing systems engineering. He lives in Upper Montclair, New Jersey.
Customer Reviews & Comments
This review is from: Data Mining: Opportunities and Challenges (Hardcover)
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.
