top

  Info

  • Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.

  Info

  • Utilizzare questo link per rimuovere la selezione effettuata.

Biblioteca

MARC Lista (tabellare)
Foundations of soft case-based reasoning [[electronic resource] /] / Sankar K. Pal, Simon C.K. Shiu
Foundations of soft case-based reasoning [[electronic resource] /] / Sankar K. Pal, Simon C.K. Shiu
Autore Pal Sankar K
Pubbl/distr/stampa Hoboken, N.J., : John Wiley & Sons, c2004
Descrizione fisica 1 online resource (298 p.)
Disciplina 006.3
Altri autori (Persone) ShiuSimon C. K
Collana Wiley series on intelligent systems
Soggetto topico Soft computing
Case-based reasoning
ISBN 1-280-36798-9
9786610367986
0-470-34668-X
0-471-64466-8
0-471-64467-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto FOUNDATIONS OF SOFT CASE-BASED REASONING; CONTENTS; FOREWORD; PREFACE; ABOUT THE AUTHORS; 1 INTRODUCTION; 1.1 Background; 1.2 Components and Features of Case-Based Reasoning; 1.2.1 CBR System versus Rule-Based System; 1.2.2 CBR versus Human Reasoning; 1.2.3 CBR Life Cycle; 1.3 Guidelines for the Use of Case-Based Reasoning; 1.4 Advantages of Using Case-Based Reasoning; 1.5 Case Representation and Indexing; 1.5.1 Case Representation; 1.5.2 Case Indexing; 1.6 Case Retrieval; 1.7 Case Adaptation; 1.8 Case Learning and Case-Base Maintenance; 1.8.1 Learning in CBR Systems
1.8.2 Case-Base Maintenance1.9 Example of Building a Case-Based Reasoning System; 1.9.1 Case Representation; 1.9.2 Case Indexing; 1.9.3 Case Retrieval; 1.9.4 Case Adaptation; 1.9.5 Case-Base Maintenance; 1.10 Case-Based Reasoning: Methodology or Technology?; 1.11 Soft Case-Based Reasoning; 1.11.1 Fuzzy Logic; 1.11.2 Neural Networks; 1.11.3 Genetic Algorithms; 1.11.4 Some CBR Tasks for Soft Computing Applications; 1.12 Summary; References; 2 CASE REPRESENTATION AND INDEXING; 2.1 Introduction; 2.2 Traditional Methods of Case Representation; 2.2.1 Relational Representation
2.2.2 Object-Oriented Representation2.2.3 Predicate Representation; 2.2.4 Comparison of Case Representations; 2.3 Soft Computing Techniques for Case Representation; 2.3.1 Case Knowledge Representation Based on Fuzzy Sets; 2.3.2 Rough Sets and Determining Reducts; 2.3.3 Prototypical Case Generation Using Reducts with Fuzzy Representation; 2.4 Case Indexing; 2.4.1 Traditional Indexing Method; 2.4.2 Case Indexing Using a Bayesian Model; 2.4.3 Case Indexing Using a Prototype-Based Neural Network; 2.4.4 Case Indexing Using a Three-Layered Back Propagation Neural Network; 2.5 Summary; References
3 CASE SELECTION AND RETRIEVAL3.1 Introduction; 3.2 Similarity Concept; 3.2.1 Weighted Euclidean Distance; 3.2.2 Hamming and Levenshtein Distances; 3.2.3 Cosine Coefficient for Text-Based Cases; 3.2.4 Other Similarity Measures; 3.2.5 k-Nearest Neighbor Principle; 3.3 Concept of Fuzzy Sets in Measuring Similarity; 3.3.1 Relevance of Fuzzy Similarity in Case Matching; 3.3.2 Computing Fuzzy Similarity Between Cases; 3.4 Fuzzy Classification and Clustering of Cases; 3.4.1 Weighted Intracluster and Intercluster Similarity; 3.4.2 Fuzzy ID3 Algorithm for Classification
3.4.3 Fuzzy c-Means Algorithm for Clustering3.5 Case Feature Weighting; 3.5.1 Using Gradient-Descent Technique and Neural Networks; 3.5.2 Using Genetic Algorithms; 3.6 Case Selection and Retrieval Using Neural Networks; 3.6.1 Methodology; 3.6.2 Glass Identification; 3.7 Case Selection Using a Neuro-Fuzzy Model; 3.7.1 Selection of Cases and Class Representation; 3.7.2 Formulation of the Network; 3.8 Case Selection Using Rough-Self Organizing Map; 3.8.1 Pattern Indiscernibility and Fuzzy Discretization of Feature Space; 3.8.2 Methodology for Generation of Reducts; 3.8.3 Rough SOM
3.8.4 Experimental Results
Record Nr. UNINA-9910143491203321
Pal Sankar K  
Hoboken, N.J., : John Wiley & Sons, c2004
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Foundations of soft case-based reasoning / / Sankar K. Pal, Simon C.K. Shiu
Foundations of soft case-based reasoning / / Sankar K. Pal, Simon C.K. Shiu
Autore Pal Sankar K
Edizione [1st ed.]
Pubbl/distr/stampa Hoboken, N.J., : John Wiley & Sons, c2004
Descrizione fisica 1 online resource (298 p.)
Disciplina 006.3
Altri autori (Persone) ShiuSimon C. K
Collana Wiley series on intelligent systems
Soggetto topico Soft computing
Case-based reasoning
ISBN 9786610367986
9781280367984
1280367989
9780470346686
047034668X
9780471644668
0471644668
9780471644675
0471644676
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto FOUNDATIONS OF SOFT CASE-BASED REASONING; CONTENTS; FOREWORD; PREFACE; ABOUT THE AUTHORS; 1 INTRODUCTION; 1.1 Background; 1.2 Components and Features of Case-Based Reasoning; 1.2.1 CBR System versus Rule-Based System; 1.2.2 CBR versus Human Reasoning; 1.2.3 CBR Life Cycle; 1.3 Guidelines for the Use of Case-Based Reasoning; 1.4 Advantages of Using Case-Based Reasoning; 1.5 Case Representation and Indexing; 1.5.1 Case Representation; 1.5.2 Case Indexing; 1.6 Case Retrieval; 1.7 Case Adaptation; 1.8 Case Learning and Case-Base Maintenance; 1.8.1 Learning in CBR Systems
1.8.2 Case-Base Maintenance1.9 Example of Building a Case-Based Reasoning System; 1.9.1 Case Representation; 1.9.2 Case Indexing; 1.9.3 Case Retrieval; 1.9.4 Case Adaptation; 1.9.5 Case-Base Maintenance; 1.10 Case-Based Reasoning: Methodology or Technology?; 1.11 Soft Case-Based Reasoning; 1.11.1 Fuzzy Logic; 1.11.2 Neural Networks; 1.11.3 Genetic Algorithms; 1.11.4 Some CBR Tasks for Soft Computing Applications; 1.12 Summary; References; 2 CASE REPRESENTATION AND INDEXING; 2.1 Introduction; 2.2 Traditional Methods of Case Representation; 2.2.1 Relational Representation
2.2.2 Object-Oriented Representation2.2.3 Predicate Representation; 2.2.4 Comparison of Case Representations; 2.3 Soft Computing Techniques for Case Representation; 2.3.1 Case Knowledge Representation Based on Fuzzy Sets; 2.3.2 Rough Sets and Determining Reducts; 2.3.3 Prototypical Case Generation Using Reducts with Fuzzy Representation; 2.4 Case Indexing; 2.4.1 Traditional Indexing Method; 2.4.2 Case Indexing Using a Bayesian Model; 2.4.3 Case Indexing Using a Prototype-Based Neural Network; 2.4.4 Case Indexing Using a Three-Layered Back Propagation Neural Network; 2.5 Summary; References
3 CASE SELECTION AND RETRIEVAL3.1 Introduction; 3.2 Similarity Concept; 3.2.1 Weighted Euclidean Distance; 3.2.2 Hamming and Levenshtein Distances; 3.2.3 Cosine Coefficient for Text-Based Cases; 3.2.4 Other Similarity Measures; 3.2.5 k-Nearest Neighbor Principle; 3.3 Concept of Fuzzy Sets in Measuring Similarity; 3.3.1 Relevance of Fuzzy Similarity in Case Matching; 3.3.2 Computing Fuzzy Similarity Between Cases; 3.4 Fuzzy Classification and Clustering of Cases; 3.4.1 Weighted Intracluster and Intercluster Similarity; 3.4.2 Fuzzy ID3 Algorithm for Classification
3.4.3 Fuzzy c-Means Algorithm for Clustering3.5 Case Feature Weighting; 3.5.1 Using Gradient-Descent Technique and Neural Networks; 3.5.2 Using Genetic Algorithms; 3.6 Case Selection and Retrieval Using Neural Networks; 3.6.1 Methodology; 3.6.2 Glass Identification; 3.7 Case Selection Using a Neuro-Fuzzy Model; 3.7.1 Selection of Cases and Class Representation; 3.7.2 Formulation of the Network; 3.8 Case Selection Using Rough-Self Organizing Map; 3.8.1 Pattern Indiscernibility and Fuzzy Discretization of Feature Space; 3.8.2 Methodology for Generation of Reducts; 3.8.3 Rough SOM
3.8.4 Experimental Results
Record Nr. UNINA-9910811879303321
Pal Sankar K  
Hoboken, N.J., : John Wiley & Sons, c2004
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui