This book constitutes the refereed proceedings of the 23rd International Conference on Case-Based Reasoning Research and Development, ICCBR 2015, held in Frankfurt am Main, Germany, in September 2015. The 26 revised full papers presented were carefully reviewed and selected from 37 submissions. The papers cover a wide range of CBR topics that are of interest both to researchers and practitioners from foundations of Case-Based Reasoning; over CBR systems for specific tasks and related fields; up to CBR systems, applications and lessons learned in specific areas of expertise such as health;…mehr
This book constitutes the refereed proceedings of the 23rd International Conference on Case-Based Reasoning Research and Development, ICCBR 2015, held in Frankfurt am Main, Germany, in September 2015. The 26 revised full papers presented were carefully reviewed and selected from 37 submissions. The papers cover a wide range of CBR topics that are of interest both to researchers and practitioners from foundations of Case-Based Reasoning; over CBR systems for specific tasks and related fields; up to CBR systems, applications and lessons learned in specific areas of expertise such as health; e-science; finance; energy, logistics, traffic; game/AI; cooking; diagnosis, technical support; as well as knowledge and experience management
Case BaseMaintenance in Preference-based CBR.- Learning to Estimate: A Case-BasedApproach to Task Execution Prediction .- Case-based Policy and GoalRecognition.- Adapting Sentiments with Context.- Aspect Selection for SocialRecommender Systems.- Music Recommendation: Audio Neighbourhoods to DiscoverMusic in the Long Tail.- Goal-Driven Autonomy with Semantically-annotatedHierarchical Cases.- Evaluating a Textual Adaptation System.- Visual CaseRetrieval for Interpreting Skill Demonstrations.- Improving Trust-GuidedBehavior Adaptation Using Operator Feedback.- Top-Down Induction of SimilarityMeasures Using Similarity Clouds.- Improving Case Retrieval Using Typicality.- CBRMeets Big Data: A Case Study of Large-Scale Adaptation Rule Generation.- Addressingthe Cold-Start Problem in Facial Expression Recognition.- Flexible FeatureDeletion: Compacting Case Bases by Selectively Compressing Case Contents.- ACase-Based Approach For Easing Schema Semantic Mapping.- Great Explanations:Opinionated Explanations for Recommendation.- Learning and Applying AdaptationOperators in Process-Oriented Case-Based Reasoning.- Fault Diagnosis via Fusionof Information from a Case Stream.- Argument-based Case Revision in CBR forStory Generation.- CBR Model for Predicting a Building's Electricity Use:On-Line Implementation in the Absence of Historical Data.- ModellingHierarchical Relationships in Group Recommender Systems.- Semi-automaticKnowledge Extraction from Semi-structured andUnstructured Data within theOMAHA Project.- Evidence-Driven Retrieval in Textual CBR: Bridging the GapBetween Retrieval and Reuse.- Maintaining and Analyzing Production Process DefinitionsUsing a Tree-Based Similarity Measure.- Case-Based Plan Recognition UnderImperfect Observability.
Case BaseMaintenance in Preference-based CBR.- Learning to Estimate: A Case-BasedApproach to Task Execution Prediction .- Case-based Policy and GoalRecognition.- Adapting Sentiments with Context.- Aspect Selection for SocialRecommender Systems.- Music Recommendation: Audio Neighbourhoods to DiscoverMusic in the Long Tail.- Goal-Driven Autonomy with Semantically-annotatedHierarchical Cases.- Evaluating a Textual Adaptation System.- Visual CaseRetrieval for Interpreting Skill Demonstrations.- Improving Trust-GuidedBehavior Adaptation Using Operator Feedback.- Top-Down Induction of SimilarityMeasures Using Similarity Clouds.- Improving Case Retrieval Using Typicality.- CBRMeets Big Data: A Case Study of Large-Scale Adaptation Rule Generation.- Addressingthe Cold-Start Problem in Facial Expression Recognition.- Flexible FeatureDeletion: Compacting Case Bases by Selectively Compressing Case Contents.- ACase-Based Approach For Easing Schema Semantic Mapping.- Great Explanations:Opinionated Explanations for Recommendation.- Learning and Applying AdaptationOperators in Process-Oriented Case-Based Reasoning.- Fault Diagnosis via Fusionof Information from a Case Stream.- Argument-based Case Revision in CBR forStory Generation.- CBR Model for Predicting a Building's Electricity Use:On-Line Implementation in the Absence of Historical Data.- ModellingHierarchical Relationships in Group Recommender Systems.- Semi-automaticKnowledge Extraction from Semi-structured andUnstructured Data within theOMAHA Project.- Evidence-Driven Retrieval in Textual CBR: Bridging the GapBetween Retrieval and Reuse.- Maintaining and Analyzing Production Process DefinitionsUsing a Tree-Based Similarity Measure.- Case-Based Plan Recognition UnderImperfect Observability.
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