Data preparation for data mining
Data preparation for data mining
Data Mining for Scientific and Engineering Applications
Data Mining for Scientific and Engineering Applications
Applications of Data Mining to Electronic Commerce
Data Mining and Knowledge Discovery
Proceedings of the 2008 conference on Applications of Data Mining in E-Business and Finance
Proceedings of the 2008 conference on Applications of Data Mining in E-Business and Finance
Best Practices for Predictive Analytics in B2B Financial Services
Proceedings of the 2010 conference on Data Mining for Business Applications
Towards the Generic Framework for Utility Considerations in Data Mining Research
Proceedings of the 2010 conference on Data Mining for Business Applications
Customer Validation of Commercial Predictive Models
Proceedings of the 2010 conference on Data Mining for Business Applications
Customer churn prediction --a case study in retail banking
Proceedings of the 2010 conference on Data Mining for Business Applications
Resource-bounded Outlier Detection using Clustering Methods
Proceedings of the 2010 conference on Data Mining for Business Applications
An Integrated System to Support Electricity Tariff Contract Definition
Proceedings of the 2010 conference on Data Mining for Business Applications
Mining Medical Administrative Data --The PKB Suite
Proceedings of the 2010 conference on Data Mining for Business Applications
Clustering of Adolescent Criminal Offenders using Psychological and Criminological Profiles
Proceedings of the 2010 conference on Data Mining for Business Applications
Forecasting Online Auctions using Dynamic Models
Proceedings of the 2010 conference on Data Mining for Business Applications
Proceedings of the 2010 conference on Data Mining for Business Applications
Spatial Data Mining in Practice: Principles and Case Studies
Proceedings of the 2010 conference on Data Mining for Business Applications
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This chapter introduces the volume on Data Mining (DM) for Business Applications. The chapters in this book provide an overview of some of the major advances in the field, namely in terms of methodology and applications, both traditional and emerging. In this introductory paper, we provide a context for the rest of the book. The framework for discussing the contents of the book is the DM methodology, which is suitable both to organize and relate the diverse contributions of the chapters selected. The chapter closes with an overview of the chapters in the book to guide the reader.