Knowledge Discovery for Business Information Systems (Hardcover, 2001)

Preface. Foreword. List of Contributors. 1. Information Filters Supplying Data Warehouses with Benchmarking Information; W. Abramowicz, et al. 2. Parallel Mining of Association Rules; D. Cheung, Sau Dan Lee. 3. Unsupervised Feature Ranking and Selection; M. Dash, et al. 4. Approaches to Concept Based Exploration of Information Resources; H.-M. Haav, J.F. Nilsson. 5. Hybrid Methodology of Knowledge Discovery for Business Information; Z.S. Hippe. 6. Fuzzy Linguistic Summaries of Databases for an Efficient Business Data Analysis and Decision Support; J. Kacprzyk, et al. 7. Integrating Data Sources Using a Standardized Global Dictionary; R. Lawrence, K. Barker. 8. Maintenance of Discovered Association Rules; Sau Dan Lee, D. Cheung. 9. Multidimensional Business Process Analysis with the Process Warehouse; B. List, et al. 10. Amalgamation of Statistics and Data Mining Techniques: Explorations in Customer Lifetime Value Modeling; D.R. Mani, et al. 11. Robust Business Intelligence Solutions; J. Mrazek. 12. The Role of Granular Information in Knowledge Discovery in Databases; W. Pedrycz. 13. Dealing with Dimensions in Data Warehousing; J. Pokorny. 14. Enhancing the KDD Process in the Relational Database Mining Framework by Quantitative Evaluation of Association Rules; G. Psaila. 15. Speeding up Hypothesis Development; J.A. Schlosser, et al. 16. Sequence Mining in Dynamic and Interactive Environments; S. Parthasarathy, et al. 17. Investigation of Artificial Neural Networks forClassifying Levels of Financial Distress of Firms: The Case of an Unbalanced Training Sample; J. Zurada, et al. Index.