Preece / Craw | Advances in Case-Based Reasoning | Buch | 978-3-540-44109-0 | sack.de

Buch, Englisch, Band 2416, 656 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 1007 g

Reihe: Lecture Notes in Artificial Intelligence

Preece / Craw

Advances in Case-Based Reasoning

6th European Conference, ECCBR 2002 Aberdeen, Scotland, UK, September 4-7, 2002 Proceedings

Buch, Englisch, Band 2416, 656 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 1007 g

Reihe: Lecture Notes in Artificial Intelligence

ISBN: 978-3-540-44109-0
Verlag: Springer Berlin Heidelberg


The papers collected in this volume were presented at the 6th European C- ference on Case-Based Reasoning (ECCBR 2002) held at The Robert Gordon University in Aberdeen, UK. This conference followed a series of very succe- ful well-established biennial European workshops held in Trento, Italy (2000), Dublin, Ireland (1998), Lausanne, Switzerland (1996), and Paris, France (1994), after the initial workshop in Kaiserslautern, Germany (1993). These meetings have a history of attracting ?rst-class European and international researchers and practitioners in the years interleaving with the biennial international co- terpart ICCBR; the 4th ICCBR Conference was held in Vancouver, Canada in 2001. Proceedings of ECCBR and ICCBR conferences are traditionally published by Springer-Verlag in their LNAI series. Case-Based Reasoning (CBR) is an AI problem-solving approach where pr- lems are solved by retrieving and reusing solutions from similar, previously solved problems, and possibly revising the retrieved solution to re?ect di?erences - tween the new and retrieved problems. Case knowledge stores the previously solved problems and is the main knowledge source of a CBR system. A main focus of CBR research is the representation, acquisition and maintenance of case knowledge. Recently other knowledge sources have been recognized as important: indexing, similarity and adaptation knowledge. Signi?cant knowledge engine- ing e?ort may be needed for these, and so the representation, acquisition and maintenance of CBR knowledge more generally have become important.
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Invited Papers.- Integrating Background Knowledge into Nearest-Neighbor Text Classification.- Applying Knowledge Management: Techniques for Building Organisational Memories.- Research Papers.- On the Complexity of Plan Adaptation by Derivational Analogy in a Universal Classical Planning Framework.- Inductive Learning for Case-Based Diagnosis with Multiple Faults.- Diverse Product Recommendations Using an Expressive Language for Case Retrieval.- Digital Image Similarity for Geo-spatial Knowledge Management.- Poetry Generation in COLIBRI.- Adaptation Using Iterated Estimations.- The Use of a Uniform Declarative Model in 3D Visualisation for Case-Based Reasoning.- Experiments on Case-Based Retrieval of Software Designs.- Exploiting Taxonomic and Causal Relations in Conversational Case Retrieval.- Bayesian Case Reconstruction.- Relations between Customer Requirements, Performance Measures, and General Case Properties for Case Base Maintenance.- Representing Temporal Knowledge for Case-Based Prediction.- Local Predictions for Case-Based Plan Recognition.- Automatically Selecting Strategies for Multi-Case-Base Reasoning.- Diversity-Conscious Retrieval.- Improving Case Representation and Case Base Maintenance in Recommender Agents.- Similarity Assessment for Generalizied Cases by Optimization Methods.- Case Acquisition in a Project Planning Environment.- Improving Case-Based Recommendation.- Efficient Similarity Determination and Case Construction Techniques for Case-Based Reasoning.- Constructive Adaptation.- A Fuzzy Case Retrieval Approach Based on SQL for Implementing Electronic Catalogs.- Integrating Hybrid Rule-Based with Case-Based Reasoning.- Search and Adaptation in a Fuzzy Object Oriented Case Base.- Deleting and Building Sort Out Techniques for Case Base Maintenance.- Entropy-Based vs. Similarity-Influenced: Attribute Selection Methods for Dialogs Tested on Different Electronic Commerce Domains.- Category-Based Filtering and User Stereotype Cases to Reduce the Latency Problem in Recommender Systems.- Defining Similarity Measures: Top-Down vs. Bottom-Up.- Learning to Adapt for Case-Based Design.- An Approach to Aggregating Ensembles of Lazy Learners That Supports Explanation.- An Experimental Study of Increasing Diversity for Case-Based Diagnosis.- Application Papers.- Collaborative Case-Based Recommender Systems.- Tuning Production Processes through a Case Based Reasoning Approach.- An Application of Case-Based Reasoning to the Adaptive Management of Wireless Networks.- A Case-Based Personal Travel Assistant for Elaborating User Requirements and Assessing Offers.- An Automated Hybrid CBR System for Forecasting.- Using CBR for Automation of Software Design Patterns.- A New Approach to Solution Adaptation and Its Application for Design Purposes.- InfoFrax: CBR in Fused Cast Refractory Manufacture.- Comparison-Based Recommendation.- Case-Based Reasoning for Estuarine Model Design.- Similarity Guided Learning of the Case Description and Improvement of the System Performance in an Image Classification System.- ITR: A Case-Based Travel Advisory System.- Supporting Electronic Design Reuse by Integrating Quality-Criteria into CBR-Based IP Selection.- Building a Case-Based Decision Support System for Land Development Control Using Land Use Function Pattern.


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