| The LNAI series reports state-of-the-art results in artificial intelligence re-search, development, and education, at a high level and in both printed and electronic form. Enjoying tight cooperation with the R&D community, with numerous individuals, as well as with prestigious organizations and societies,LNAI has grown into the most comprehensive artificial intelligence research forum available. The scope of LNAI spans the whole range of artificial intelligence and intelli-gent information processing including interdisciplinary topics in a variety of application fields. The type of material published traditionally includes -proceedings (published in time for the respective conference) -post-proceedings (consisting of thoroughly revised final full papers) -research monographs (which may be based on PhD work) |
| Invited Papers Knowledge-Intensive Case-Based Reasoning in CREEK Designing Industrial Case-Based Reasoning Applications Research Papers Maintaining Case-Based Reasoning Systems:A Machine Learning Approach JColibri: An Object-Oriented Framework for Building CBR Systems Memoire: Case Based Reasoning Meets the Semantic Web in Biology and Medicine Facilitating CBR for Incompletely-Described Cases:Distance Metrics for Partial Problem Descriptions Dialogue Management for Conversational Case-Based Reasoning Hybrid Recommender Systems with Case-Based Components Measures of Solution Accuracy in Case-Based Reasoning Systems Representing Similarity for CBR in XML An Analysis of Case-Base Editing in a Spare Filtering System A Case Based Reasoning Approach to Story Plot Generation Explanation Oriented Retrieval Exploiting Background Knowledge when Learning Similarity Measures Software Design Retrieval Using Bayesian Networks and WordNet Case-Base Injection Schemes to Case Adaptation Using Genetic Algorithms Learning Feature Taxonomies for Case Indexing Maintenance Memories: Beyond Concepts and Techniques for Case Base Maintenance Textual Reuse for Email Response Case-Based, Decision-Theoretic, HTN Planning Using CBR in the Exploration of Unknown Environments with an Autonomous Agent Ceaseless Case-Based Reasoning Explanation Service for Complex CBR Applications Explaining the Pros and Cons of Conclusions in CBR Incremental Relaxation of Unsuccessful Queries Justification-Based Case Retention Case Retrieval Using Nonlinear Feature-Space Transformation Case-Based Object Recognition …… Application Papers Author Index |
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