Advances in case-based reasoning : 5th European workshop, EWCBR 2000 Trento, Italy, September 6-9, 2000 : proceedings
Kaydedildi:
| Yazar: | |
|---|---|
| Diğer Yazarlar: | |
| Materyal Türü: | Livre numérique |
| Dil: | Anglais |
| Baskı/Yayın Bilgisi: |
Berlin [etc.] :
Springer
[20..].
Cham : Springer Nature |
| Seri Bilgileri: | Lecture notes in computer science. Lecture notes in artificial intelligence
1898 |
| Konular: | |
| Online Erişim: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Not: |
Actes d'un séminaire tenu à Trento du 6 au 9 septembre 2000, d'après l écran-titre Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Advances in case-based reasoning, 5th European workshop, EWCBR 2000, Trento, Italy, September 6-9, 2000, proceedings, Enrico Blanzieri, Luigi Portinale (eds.), 2000, New York, Springer, 1 vol. (XII-530 p.), Lecture notes in computer science, 3-540-67933-2 • Advances in Case-Based Reasoning, Texte imprimé, 9783662214329 |
İçindekiler:
- Invited Papers
- Competence Models and Their Applications
- Activating Case-Based Reasoning with Active Databases
- Research Papers
- Case-Based Reasoning with Confidence
- Combining Rule-Based and Case-Based Learning for Iterative Part-of-Speech Tagging
- An Architecture for Knowledge Intensive CBR Systems
- A Dynamic Approach to Reducing Dialog in On-Line Decision Guides
- Flexible Control of Case-Based Prediction in the Framework of Possibility Theory
- Partial Orders and Indifference Relations: Being Purposefully Vague in Case-Based Retrieval
- Representing Knowledge for Case-Based Reasoning: The Rocade System
- Personalized Conversational Case-Based Recommendation
- Learning User Preferences in Case-Based Software Reuse
- A Method for Predicting Solutions in Case-Based Problem Solving
- Genetic Algorithms to Optimise CBR Retrieval
- An Unsupervised Bayesian Distance Measure
- Remembering Why to Remember: Performance-Guided Case-Base Maintenance
- Case-Based Reasoning for Breast Cancer Treatment Decision Helping
- Competence-Guided Case-Base Editing Techniques
- Intelligent Case-Authoring Support in CaseMaker-2
- Integrating Conversational Case Retrieval with Generative Planning
- A Symmetric Nearest Neighbor Learning Rule
- Automatic Case Base Management in a Multi-modal Reasoning System
- On Quality Measures for Case Base Maintenance
- A New Approach for the Incremental Development of Adaptation Functions for CBR
- An Efficient Approach to Similarity-Based Retrieval on Top of Relational Databases
- Maintaining Case-Based Reasoning Systems Using Fuzzy Decision Trees
- Applying Recursive CBR for the Customization of Structured Products in an Electronic Shop
- Handling Vague and Qualitative Criteria in Case-Based Reasoning Applications
- Active Delivery for Lessons Learned Systems
- Application Papers
- KM-PEB: An Online Experience Base on Knowledge Management Technology
- A Support System Based on CBR for the Design of Rubber Compounds in Motor Racing
- Supporting Tourism Culture via CBR
- A Case-Based Reasoning Approach to Collaborative Filtering
- Similarity Measures for Structured Representations: A Definitional Approach
- Collaborative Maintenance - A Distributed, Interactive Case-Base Maintenance Strategy
- A Unified CBR Architecture for Robot Navigation
- Maintenance of a Case-Base for the Retrieval of Rotationally Symmetric Shapes for the Design of Metal Castings
- Personalised Route Planning: A Case-Based Approach
- A Case-Based Approach to Image Recognition
- The Life Cycle of Test Cases in a CBR System
- Evaluating a Multi-modal Reasoning System in Diabetes Care
- CBR-Based Ultra Sonic Image Interpretation
- Evaluation of Strategies for Generalised Cases within a Case-Based Reasoning Antibiotics Therapy Advice System
- A Product Customization Module Based on Adaptation Operators for CBR Systems in E-Commerce Environments
- Selecting and Comparing Multiple Cases to Maximise Result Quality after Adaptation in Case-Based Adaptive Scheduling.