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Data Mining: Opportunities and Challenges

ISBN: 1591400511
EAN: 2147483647

Year: 2003
Pages: 194

Authors: John Wang

BUY ON AMAZON

• Back Cover
• Table of Contents
• Data MiningOpportunities and Challenges
• Preface
• Chapter I: A Survey of Bayesian Data Mining
• SCHOOLS OF STATISTICS
• DATA MODEL
• LOCAL GRAPHICAL MODEL CHOICE
• GLOBAL GRAPHICAL MODEL CHOICE
• NON-CATEGORICAL VARIABLES
• CASE 1: PERSONALIZED MEDIA DISTRIBUTION
• CASE 2: SCHIZOPHRENIA RESEARCH - CAUSALITY IN COMPLEX SYSTEMS
• CONCLUSIONS
• ACKNOWLEDGMENTS
• REFERENCES
• Chapter II: Control of Inductive Bias in Supervised Learning Using Evolutionary ComputationA Wrapper-Based Approach
• BACKGROUND
• METHODOLOGIES
• RESULTS
• ACKNOWLEDGMENTS
• ENDNOTES
• REFERENCES
• Chapter III: Cooperative Learning and Virtual Reality-Based Visualization for Data Mining
• COOPERATIVE DATA MINING
• VISUAL DATA MINING
• THREE-DIMENSIONAL VISUALIZATION, VIRTUAL REALITY AND DATA MINING
• CONCLUSIONS
• REFERENCES
• Chapter IV: Feature Selection in Data Mining
• EVOLUTIONARY LOCAL SELECTION ALGORITHMS (ELSA)
• FEATURE SELECTION IN SUPERVISED LEARNING
• FEATURE SELECTION IN UNSUPERVISED LEARNING
• FEATURE SELECTION FOR ENSEMBLES
• CONCLUSIONS
• ENDNOTES
• REFERENCES
• Chapter V: Parallel and Distributed Data Mining through Parallel Skeletons and Distributed Objects
• PARALLEL AND DISTRIBUTED DATA MINING
• STRUCTURED PARALLEL PROGRAMMING
• STRUCTURED PARALLEL DATA MINING ALGORITHMS
• ADVANTAGES OF STRUCTURE PARALLELISM
• CONCLUSIONS
• REFERENCES
• Chapter VI: Data Mining Based on Rough Sets
• ROUGH SET THEORY
• VARIABLE PRECISION ROUGH SET MODEL (VPRSM)
• DATA MINING SYSTEM LERS
• APPLICATIONS
• CONCLUSIONS
• REFERENCES
• Chapter VII: The Impact of Missing Data on Data Mining
• DATA MINING WITH INCONSISTENT DATAMISSING DATA
• METHODS OF ADDRESSING MISSING DATA
• THE IMPACT OF MISSING DATA ON DATA-MINING ALGORITHMS
• FUTURE TRENDS
• CONCLUSIONS
• REFERENCES
• Chapter VIII: Mining Text Documents for Thematic Hierarchies Using Self-Organizing Maps
• RELATED WORK
• GENERATING CLUSTERS
• DEVELOPING THEMATIC HIERARCHIES FOR TEXT DOCUMENTS
• EXPERIMENTAL RESULTS
• FUTURE WORK
• CONCLUSIONS
• REFERENCES
• Chapter IX: The Pitfalls of Knowledge Discovery in Databases and Data Mining
• ORGANIZATIONAL ISSUES
• STATISTICAL ISSUES
• DATA ACCURACY AND STANDARDIZATION
• TECHNICAL ISSUES
• CONCLUSION
• REFERENCES
• Chapter X: Maximum Performance Efficiency Approaches for Estimating Best Practice Costs
• MOTIVATION
• BASIC COST MODELS AND ESTIMATION MODELS
• APPLICATION TO THE DATA
• ESTIMATION CRITERION QUALITY ISSUES
• LIMITATIONS
• EXTENSIONS TO OTHER BASIC COST MODELS
• DATA-MINING APPLICATIONS AND CONSIDERATIONS
• CONCLUSIONS
• REFERENCES
• APPENDIX
• Chapter XI: Bayesian Data Mining and Knowledge Discovery
• THE BAYESIAN APPROACH TO PROBABILITY
• BAYESIAN CLASSIFICATION
• BAYESIAN BELIEF NETWORKS
• MARKOV CHAIN MONTE CARLO TECHNIQUES
• CONCLUDING REMARKS
• ENDNOTES
• REFERENCES
• Chapter XII: Mining Free Text for Structure
• RELATED WORK
• MINING NEWSGROUPS EXPERTISE
• MINING FAQS FOR STRUCTURE
• EVALUATION
• FUTURE TRENDS
• CONCLUSION
• ENDNOTES
• ACKNOWLEDGMENTS
• REFERENCES
• APPENDIX
• Chapter XIII: Query-By-Structure Approach for the Web
• BACKGROUND
• QUERY-BY-STRUCTURE SYSTEMS
• FUTURE TRENDS
• CONCLUSION
• REFERENCES
• Chapter XIV: Financial Benchmarking Using Self-Organizing MapsStudying the International Pulp and Paper Industry
• METHODOLOGY
• COMPANIES INCLUDED
• CONSTRUCTING THE MAPS
• RESULTS
• CONCLUSIONS
• FUTURE RESEARCH IN THIS AREA
• ACKNOWLEDGMENTS
• REFERENCES
• APPENDIX: THE FEATURE PLANES OF THE FINAL MAP
• Chapter XV: Data Mining in Health Care Applications
• DATA MINING IN HEALTH CARE
• COMMUNITY HEALTH INFORMATION NETWORKS (CHINS)
• FINDINGS USING A CASE METHODOLOGY
• HOW THE PLATFORM CAN BE USED
• DATA-MINING IMPLICATIONS: CONTROVERSIES AND ISSUES ASSOCIATED WITH CHINS
• CONCLUSION
• ENDNOTE
• REFERENCES
• Chapter XVI: Data Mining for Human Resource Information Systems
• BACKGROUND
• APPLYING DATA MINING TECHNIQUES TO HR INFORMATION SYSTEMS
• PRACTICAL APPLICATIONS OF DATA MINING HR INFORMATION
• CONCLUSIONS
• REFERENCES
• Chapter XVII: Data Mining in Information Technology and Banking Performance
• DATA ENVELOPMENT ANALYSIS
• THE MODEL
• APPLICATION
• CONCLUSIONS
• REFERENCES
• Chapter XVIII: Social, Ethical and Legal Issues of Data Mining
• WHAT CAN BE INFERRED FROM DATA?
• ETHICAL ISSUES
• SOCIAL IMPLICATIONS
• LEGAL ISSUES
• FUTURE TRENDS
• CONCLUSION
• REFERENCES
• Chapter XIX: Data Mining in Designing an Agent-Based DSS
• USE OF DATA MINING IN DESIGNING THE SYSTEM KNOWLEDGE BASE
• USE OF DATA MINING IN DESIGNING THE LEARNING PROCESS
• MULTIAGENT-BASED ARCHITECTURE FOR THE DYNAMIC DSS
• CONCLUSIONS
• REFERENCES
• Chapter XX: Critical and Future Trends in Data Mining-A Review of Key Data Mining TechnologiesApplications
• TEXT DATA MINING (TDM)
• DISTRIBUTEDCOLLECTIVE DM
• UBIQUITOUS DM (UDM)
• HYPERTEXT AND HYPERMEDIA DATA MINING
• VISUAL DM
• MULTIMEDIA DM
• SPATIAL AND GEOGRAPHIC DM
• TIME SERIESSEQUENCE DM
• DM TRENDS: METHODS AND TECHNIQUES
• DM FOR BIOINFORMATICS
• SUMMARY
• REFERENCES
• Index
• Index A
• Index B
• Index C
• Index D
• Index E
• Index F
• Index G
• Index H
• Index I
• Index J
• Index K
• Index L
• Index M
• Index N
• Index O
• Index P
• Index Q
• Index R
• Index S
• Index T
• Index U
• Index V
• Index W
• Index X-Y
• Index Z
• List of Figures