Relational Data Mining
As the first book devoted to relational data mining, this coherently written multi-author monograph provides a thorough introduction and systematic overview of the area. The first part introduces the reader to the basics and principles of classical knowledge discovery in databases and inductive logi...
| Other Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
Berlin, Heidelberg
Springer Berlin Heidelberg
2001, 2001
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| Edition: | 1st ed. 2001 |
| Subjects: | |
| Online Access: | |
| Collection: | Springer Book Archives -2004 - Collection details see MPG.ReNa |
Table of Contents:
- I. Introduction
- 1. Data Mining in a Nutshell
- 2. Knowledge Discovery in Databases: An Overview
- 3. An Introduction to Inductive Logic Programming
- 4. Inductive Logic Programming for Knowledge Discovery in Databases
- II. Techniques
- 5. Three Companions for Data Mining in First Order Logic
- 6. Inducing Classification and Regression Trees in First Order Logic
- 7. Relational Rule Induction with CProgol4.4: A Tutorial Introduction
- 8. Discovery of Relational Association Rules
- 9. Distance Based Approaches to Relational Learning and Clustering
- III. From Propositional to Relational Data Mining
- 10. How to Upgrade Propositional Learners to First Order Logic: A Case Study
- 11. Propositionalization Approaches to Relational Data Mining
- 12. Relational Learning and Boosting
- 13. Learning Probabilistic Relational Models
- IV. Applications and Web Resources
- 14. Relational Data Mining Applications: An Overview
- 15. Four Suggestions and a Rule Concerning the Application of ILP
- 16. Internet Resources on ILP for KDD
- Author Index