Overview
Data Mining introduces in clear and simple ways how to use existing data mining methods to obtain effective solutions for a variety of management and engineering design problems. Data Mining is organised into two parts: the first provides a focused introduction to data mining and the second goes into greater depth on subjects such as customer analysis. It covers almost all managerial activities of a company, including: • supply chain design, • product development, • manufacturing system design, • product quality control, and • preservation of privacy. Incorporating recent developments of data mining that have made it possible to deal with management and engineering design problems with greater efficiency and efficacy, Data Mining presents a number of state-of-the-art topics. It will be an informative source of information for researchers, but will also be a useful reference work for industrial and managerial practitioners.
Full Product Details
Author: Yong Yin ,
Ikou Kaku ,
Jiafu Tang ,
JianMing Zhu
Publisher: Springer London Ltd
Imprint: Springer London Ltd
Edition: 2011 ed.
Dimensions:
Width: 15.50cm
, Height: 1.80cm
, Length: 23.50cm
Weight: 0.504kg
ISBN: 9781447161189
ISBN 10: 1447161181
Pages: 312
Publication Date: 26 November 2014
Audience:
Professional and scholarly
,
Professional & Vocational
Format: Paperback
Publisher's Status: Active
Availability: Manufactured on demand
We will order this item for you from a manufactured on demand supplier.
Reviews
From the reviews: The book is a combination of a textbook and a collection of papers. ... useful for industrial and managerial practitioners who want to understand DM-related methods and how they could use DM to support their decisions. Beginning researchers might also benefit because the book reflects the diversity of DM methods without providing complex details of the algorithms. ... this book will inspire and motivate decision makers to consider DM as a useful approach for solving some decision problems. (Robert Stahlbock, Interfaces, Vol. 42 (4), July-August, 2012) The authors spend the first six chapters of this book introducing the various methods of data analysis, focusing on programming algorithms for data mining related to the fields of business management and engineering design. ... Each chapter ends with a number of references that provide additional resources for those who wish to explore the issues further. ... I recommend this book to practitioners and researchers who are interested in data mining applications for business management and engineering design. (E. Y. Lee, ACM Computing Reviews, June, 2011)
From the reviews: The book is a combination of a textbook and a collection of papers. useful for industrial and managerial practitioners who want to understand DM-related methods and how they could use DM to support their decisions. Beginning researchers might also benefit because the book reflects the diversity of DM methods without providing complex details of the algorithms. this book will inspire and motivate decision makers to consider DM as a useful approach for solving some decision problems. (Robert Stahlbock, Interfaces, Vol. 42 (4), July-August, 2012) The authors spend the first six chapters of this book introducing the various methods of data analysis, focusing on programming algorithms for data mining related to the fields of business management and engineering design. Each chapter ends with a number of references that provide additional resources for those who wish to explore the issues further. I recommend this book to practitioners and researchers who are interested in data mining applications for business management and engineering design. (E. Y. Lee, ACM Computing Reviews, June, 2011)
Author Information
Yong Yin has been Associate Professor at Yamagata University, Japan, since 2004. He was previously Assistant Professor at the same university from 2002 to 2004. His research areas are manufacturing strategy; product development; workforce agility; and supply chain management. Ikou Kaku is a professor at the Department of Management Science and Engineering, Akita Prefectural University, Japan. His research interests are in human factors related to manufacturing; mathematical modeling and meta heuristics; data mining techniques and their application in inventory management; and supply chain management. Jiafu Tang is a professor at Northeastern University, Shenyang, China. He works in the Institute of Systems Engineering's Key Laboratory of Integrated Automation of Process Industry of MOE. JianMing Zhu is a professor at the Central University of Finance and Economics, Beijing, China. He works in the School of Information.
