Data Mining : Opportunities and Challenges Book

	Preface
Ch. I	A Survey of Bayesian Data Mining	1
Ch. II	Control of Inductive Bias in Supervised Learning Using Evolutionary Computation: A Wrapper-Based Approach	27
Ch. III	Cooperative Learning and Virtual Reality-Based Visualization for Data Mining	55
Ch. IV	Feature Selection in Data Mining	80
Ch. V	Parallel and Distributed Data Mining through Parallel Skeletons and Distributed Objects	106
Ch. VI	Data Mining Based on Rough Sets	142
Ch. VII	The Impact of Missing Data on Data Mining	174
Ch. VIII	Mining Text Documents for Thematic Hierarchies Using Self-Organizing Maps	199
Ch. IX	The Pitfalls of Knowledge Discovery in Databases and Data Mining	220
Ch. X	Maximum Performance Efficiency Approaches for Estimating Best Practice Costs	239
Ch. XI	Bayesian Data Mining and Knowledge Discovery	260
Ch. XII	Mining Free Text for Structure	278
Ch. XIII	Query-By-Structure Approach for the Web	301
Ch. XIV	Financial Benchmarking Using Self-Organizing Maps - Studying the International Pulp and Paper Industry	323
Ch. XV	Data Mining in Health Care Applications	350
Ch. XVI	Data Mining for Human Resource Information Systems	366
Ch. XVII	Data Mining in Information Technology and Banking Performance	382
Ch. XVIII	Social, Ethical and Legal Issues of Data Mining	395
Ch. XIX	Data Mining in Designing an Agent-Based DSS	421
Ch. XX	Critical and Future Trends in Data Mining: A Review of Key Data Mining Technologies/Applications	437
	About the Authors	453
	Index	462