Intelligent Data Mining: Techniques and Applications (Studies in Computational Intelligence (5))

__Intelligent Data Mining - Techniques and Applications__ is an organized edited collection of contributed chapters covering basic knowledge for intelligent systems and data mining, applications in economic and management, industrial engineering and other related industrial applications. The main objective of this book is to gather a number of peer-reviewed high quality contributions in the relevant topic areas. The focus is especially on those chapters that provide theoretical/analytical solutions to the problems of real interest in intelligent techniques possibly combined with other traditional tools, for data mining and the corresponding applications to engineers and managers of different industrial sectors. Academic and applied researchers and research students working on data mining can also directly benefit from this book. Some Considerations in Multi-Source Data Fusion....Pages 1-22 Granular Nested Causal Complexes....Pages 23-48 Gene Regulating Network Discovery....Pages 49-78 Semantic Relations and Information Discovery....Pages 79-102 Sequential Pattern Mining * ....Pages 103-122 Uncertain Knowledge Association Through Information Gain....Pages 123-135 Data Mining for Maximal Frequent Patterns in Sequence Groups....Pages 137-161 Mining Association Rules with Rough Sets....Pages 163-184 The Evolution of the Concept of Fuzzy Measure....Pages 185-200 Association Rule Based Specialization in ER Models....Pages 201-217 Discovering the Factors Affecting the Location Selection of FDI in China * ....Pages 219-236 Penalty-Reward Analysis with Uninorms: A Study of Customer (Dis)Satisfaction....Pages 237-252 Using an Adapted Classification Based on Associations Algorithm in an Activity-Based Transportation System....Pages 253-265 Evolutionary Induction of Descriptive Rules in a Market Problem....Pages 267-292 Personalized Multi-Stage Decision Support in Reverse Logistics Management....Pages 293-312 Fuzzy Process Control with Intelligent Data Mining....Pages 313-336 Accelerating the New Product Introduction with Intelligent Data Mining....Pages 337-354 Integrated Clustering Modeling with Backpropagation Neural Network for Effcient Customer Relationship Management....Pages 355-373 Sensory Quality Management and Assessment: from Manufacturers to Consumers....Pages 375-400 Simulated Annealing Approach for the Multi-objective Facility Layout Problem....Pages 401-418 Self-Tuning Fuzzy Rule Bases with Belief Structure....Pages 419-437 A User Centred Approach to Management Decision Making....Pages 439-461 Techniques to Improve Multi-Agent Systems for Searching and Mining the Web....Pages 463-486 Advanced Simulator Data Mining for Operators’ Performance Assessment....Pages 487-514

intelligent Data Mining – Techniques And Applications Is An Organized Edited Collection Of Contributed Chapters Covering Basic Knowledge For Intelligent Systems And Data Mining, Applications In Economic And Management, Industrial Engineering And Other Related Industrial Applications. The Main Objective Of This Book Is To Gather A Number Of Peer-reviewed High Quality Contributions In The Relevant Topic Areas. The Focus Is Especially On Those Chapters That Provide Theoretical/analytical Solutions To The Problems Of Real Interest In Intelligent Techniques Possibly Combined With Other Traditional Tools, For Data Mining And The Corresponding Applications To Engineers And Managers Of Different Industrial Sectors. Academic And Applied Researchers And Research Students Working On Data Mining Can Also Directly Benefit From This Book.