E-Book Overview
The main goal of the new field of data mining is the analysis of large and complex datasets. Some very important datasets may be derived from business and industrial activities. This kind of data is known as enterprise data . The common characteristic of such datasets is that the analyst wishes to analyze them for the purpose of designing a more cost-effective strategy for optimizing some type of performance measure, such as reducing production time, improving quality, eliminating wastes, or maximizing profit. Data in this category may describe different scheduling scenarios in a manufacturing environment, quality control of some process, fault diagnosis in the operation of a machine or process, risk analysis when issuing credit to applicants, management of supply chains in a manufacturing system, or data for business related decision-making. Contents: Enterprise Data Mining: A Review and Research Directions (T W Liao); Application and Comparison of Classification Techniques in Controlling Credit Risk (L Yu et al.); Predictive Classification with Imbalanced Enterprise Data (S Daskalaki et al.); Data Mining Applications of Process Platform Formation for High Variety Production (J Jiao & L Zhang); Multivariate Control Charts from a Data Mining Perspective (G C Porzio & G Ragozini); Maintenance Planning Using Enterprise Data Mining (L P Khoo et al.); Mining Images of Cell-Based Assays (P Perner); Support Vector Machines and Applications (T B Trafalis & O O Oladunni); A Survey of Manifold-Based Learning Methods (X Huo et al.); and other papers.
E-Book Content
Recent Advances in Data Mining of Enterprise Data: Algorithms and Applications 6689tp.indd 1 11/26/07 4:11:02 PM Series on Computers and Operations Research Series Editor: P. M. Pardalos (University of Florida) Published Vol. 1 Optimization and Optimal Control eds. P. M. Pardalos, I. Tseveendorj and R. Enkhbat Vol. 2 Supply Chain and Finance eds. P. M. Pardalos, A. Migdalas and G. Baourakis Vol. 3 Marketing Trends for Organic Food in the 21st Century ed. G. Baourakis Vol. 4 Theory and Algorithms for Cooperative Systems eds. D. Grundel, R. Murphey and P. M. Pardalos Vol. 5 Application of Quantitative Techniques for the Prediction of Bank Acquisition Targets by F. Pasiouras, S. K. Tanna and C. Zopounidis Vol. 6 Recent Advances in Data Mining of Enterprise Data: Algorithms and Applications eds. T. Warren Liao and Evangelos Triantaphyllou Vol. 7 Computer Aided Methods in Optimal Design and Operations eds. I. D. L. Bogle and J. Zilinskas Steven - Recent Adv in Data.pmd 1 12/4/2007, 1:51 PM Series on Computers and Operations Research Vol. 6 Recent Advances in Data Mining of Enterprise Data: Algorithms and Applications T Warren Liao Evangelos Triantaphyllou Louisiana State University, USA World Scientific NEW JERSEY 6689tp.indd 2 • LONDON • SINGAPORE • BEIJING • SHANGHAI • HONG KONG • TA I P E I • CHENNAI 11/26/07 4:11:03 PM Published by World Scientific Publishing Co. Pte. Ltd. 5 Toh Tuck Link, Singapore 596224 USA office: 27 Warren Street, Suite 401-402, Hackensack, NJ 07601 UK office: 57 Shelton Street, Covent Garden, London WC2H 9HE British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library. RECENT ADVANCES IN DATA MINING OF ENTERPRISE DATA: Algorithms and Applications Series on Computers and Operations Research — Vol. 6 Copyright © 2007 by World Scientific Publishing Co. Pte. Ltd. All rights reserved. This book, or parts thereof, may not be re