Portinale / Blanzieri | Advances in Case-Based Reasoning | Buch | 978-3-540-67933-2 | sack.de

Buch, Englisch, 536 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1690 g

Reihe: Lecture Notes in Artificial Intelligence

Portinale / Blanzieri

Advances in Case-Based Reasoning

5th European Workshop, EWCBR 2000 Trento, Italy, September 6-9, 2000 Proceedings
2000
ISBN: 978-3-540-67933-2
Verlag: Springer Berlin Heidelberg

5th European Workshop, EWCBR 2000 Trento, Italy, September 6-9, 2000 Proceedings

Buch, Englisch, 536 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1690 g

Reihe: Lecture Notes in Artificial Intelligence

ISBN: 978-3-540-67933-2
Verlag: Springer Berlin Heidelberg


thanks for the support provided by EWCBR-98, MLNET,theItalianAssociationforArti?cialIntelligence(AI*IA)andthe- partmentofAdvancedSciencesandTechnologies(DISTA)oftheUniversityof EasternPiedmont(Universit` adelPiemonteOrientale”A.Avogadro”).Aspecial thanktotheinvitedspeakersBarrySmythandQiangYangandtoallthechairs ofthesessionsand?nally,toSpringer-Verlagfortheirhelpandtheirenthusiastic agreementon the publication of this volume.

Portinale / Blanzieri Advances in Case-Based Reasoning jetzt bestellen!

Zielgruppe


Research

Weitere Infos & Material


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.



Ihre Fragen, Wünsche oder Anmerkungen
Vorname*
Nachname*
Ihre E-Mail-Adresse*
Kundennr.
Ihre Nachricht*
Lediglich mit * gekennzeichnete Felder sind Pflichtfelder.
Wenn Sie die im Kontaktformular eingegebenen Daten durch Klick auf den nachfolgenden Button übersenden, erklären Sie sich damit einverstanden, dass wir Ihr Angaben für die Beantwortung Ihrer Anfrage verwenden. Selbstverständlich werden Ihre Daten vertraulich behandelt und nicht an Dritte weitergegeben. Sie können der Verwendung Ihrer Daten jederzeit widersprechen. Das Datenhandling bei Sack Fachmedien erklären wir Ihnen in unserer Datenschutzerklärung.