Knowledge Discovery in Multiple Databases

1. Importance of Multi-database Mining. - 1. 1 Introduction. - 1. 2 Role of Multi-database Mining in Real-world Applications. - 1. 3 Multi-database Mining Problems. - 1. 4 Differences Between Mono- and Multi-database Mining. - 1. 5 Evolution of Multi-database Mining. - 1. 6 Limitations of Previous Techniques. - 1. 7 Process of Multi-database Mining. - 1. 8 Features of the Defined Process. - 1. 9 Major Contributions of This Book. - 1. 10 Organization of the Book. - 2. Data Mining and Multi-database Mining. - 2. 1 Introduction. - 2. 2 Knowledge Discovery in Databases. - 2. 3 Association Rule Mining. - 2. 4 Research into Mining Mono-databases. - 2. 5 Research into Mining Multi-databases. - 2. 6 Summary. - 3. Local Pattern Analysis. - 3. 1 Introduction. - 3. 2 Previous Multi-database Mining Techniques. - 3. 3 Local Patterns. - 3. 4 Local Instance Analysis Inspired by Competition in Sports. - 3. 5 The Structure of Patterns in Multi-database Environments. - 3. 6 Effectiveness of Local Pattern Analysis. - 3. 7 Summary. - 4. Identifying Quality Knowledge. - 4. 1 Introduction. - 4. 2 Problem Statement. - 4. 3 Nonstandard Interpretation. - 4. 4 Proof Theory. - 4. 5 Adding External Knowledge. - 4. 6 The Use of the Framework. - 4. 7 Summary. - 5. Database Clustering. - 5. 1 Introduction. - 5. 2 Effectiveness of Classifying. - 5. 3 Classifying Databases. - 5. 4 Searching for a Good Classification. - 5. 5 Algorithm Analysis. - 5. 6 Evaluation of Application-independent Database Classification. - 5. 7 Summary. - 6. Dealing with Inconsistency. - 6. 1 Introduction. - 6. 2 Problem Statement. - 6. 3 Definitions of Formal Semantics. - 6. 4 Weighted Majority. - 6. 5 Mastering Local Pattern Sets. - 6. 6 Examples of Synthesizing Local Pattern Sets. - 6. 7 A Syntactic Characterization. - 6. 8 Summary. - 7. Identifying High-vote Patterns. - 7. 1 Introduction. - 7. 2 Illustration of High-votePatterns. - 7. 3 Identifying High-vote Patterns. - 7. 4 Algorithm Design. - 7. 5 Identifying High-vote Patterns Using a Fuzzy Logic Controller. - 7. 6 High-vote Pattern Analysis. - 7. 7 Suggested Patterns. - 7. 8 Summary. - 8. Identifying Exceptional Patterns. - 8. 1 Introduction. - 8. 2 Interesting Exceptional Patterns. - 8. 3 Algorithm Design. - 8. 4 Identifying Exceptions with a Fuzzy Logic Controller. - 8. 5 Summary. - 9. Synthesizing Local Patterns by Weighting. - 9. 1 Introduction. - 9. 2 Problem Statement. - 9. 3 Synthesizing Rules by Weighting. - 9. 4 Improvement of Synthesizing Model. - 9. 5 Algorithm Analysis. - 9. 6 Summary. - 10. Conclusions and Future Work. - 10. 1 Conclusions. - 10. 2 Future Work. - References. Language: English