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More About This Textbook
Overview
This book outlines the core theory and practice of data mining and knowledge discovery (DM & KD) examining theoretical foundations for various methods, and presenting an array of examples, many drawn from real-life applications. Most theoretical developments are accompanied by extensive empirical analysis, offering a deep insight into both theoretical and practical aspects of the subject. The book presents the combined research experiences of 40 expert contributors of world renown.
Product Details
Related Subjects
Table of Contents
List of Figures
List of Tables
Foreword by Panos M. Pardalos
Preface
Acknowledgements
Chapter 1. A COMMON LOGIC APPROACH TO DATA MINING AND PATTERN RECOGNITION, by A. Zakrevskij
Chapter 2. THE ONE CLAUSE AT A TIME (OCAT) APPROACH TO DATA MINING AND KNOWLEDGE DISCOVERY, by E. Triantaphyllou
Chapter 3. AN INCREMENTAL LEARNING ALGORITHM FOR INFERRING LOGICAL RULES FROM EXAMPLES IN THE FRAMEWORK OF THE COMMON REASONING PROCESS, by X. Naidenova
Chapter 4. DISCOVERING RULES THAT GOVERN MONOTONE PHENOMENA, by V.I. Torvik and E. Triantaphyllou
Chapter 5. LEARNING LOGIC FORMULAS AND RELATED ERROR DISTRIBUTIONS, by G. Felici, F. Sun, and K. Truemper
Chapter 6. FEATURE SELECTION FOR DATA MINING by V. de Angelis, G. Felici, and G. Mancinelli
Chapter 7. TRANSFORMATION OF RATIONAL AND SET DATA TO LOGIC DATA, by S. Bartnikowski, M. Granberry, J. Mugan, and K. Truemper
Chapter 8. DATA FARMING: CONCEPTS AND METHODS, by A. Kusiak
Chapter 9. RULE INDUCTION THROUGH DISCRETE SUPPORT VECTOR DECISION TREES, by C. Orsenigo and C. Vercellis
Chapter 10. MULTI-ATTRIBUTE DECISION TREES AND DECISION RULES, by J.-Y. Lee and S. Olafsson
Chapter 11. KNOWLEDGE ACQUISITION AND UNCERTAINTY IN FAULT DIAGNOSIS: A ROUGH SETS PERSPECTIVE, by L.-Y. Zhai, L.-P. Khoo, and S.-C. Fok
Chapter 12. DISCOVERING KNOWLEDGE NUGGETS WITH A GENETIC ALGORITHM, by E. Noda and A.A. Freitas
Chapter 13. DIVERSITY MECHANISMS IN PITT-STYLE EVOLUTIONARY CLASSIFIER SYSTEMS, by M. Kirley, H.A. Abbass and R.I. McKay
Chapter 14. FUZZY LOGIC IN DISCOVERING ASSOCIATION RULES: AN OVERVIEW, by G. Chen, Q. Wei and E.E. Kerre
Chapter 15. MINING HUMAN INTERPRETABLE KNOWLEDGE WITH FUZZY MODELING METHODS: AN OVERVIEW, by T.W. Liao
Chapter 16. DATA MINING FROM MULTIMEDIA PATIENT RECORDS, by A.S. Elmaghraby, M.M. Kantardzic, and M.P. Wachowiak
Chapter 17. LEARNING TO FIND CONTEXT BASED SPELLING ERRORS, by H. Al-Mubaid and K. Truemper
Chapter 18. INDUCTION AND INFERENCE WITH FUZZY RULES FOR TEXTUAL INFORMATION RETRIEVAL, by J. Chen, D.H. Kraft, M.J. Martin-Bautista, and M.-A. Vila
Chapter 19. STATISTICAL RULE INDUCTION IN THE PRESENCE OF PRIOR INFORMATION: THE BAYESIAN RECORD LINKAGE PROBLEM, by D.H. Judson
Chapter 20. FUTURE TRENDS IN SOME DATA MINING AREAS, by X. Wang, P. Zhu, G. Felici, and E. Triantaphyllou
Subject Index
Author Index
Contributor Index
About the Editors