Case-Based Reasoning Research and Development

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

Includes supplementary material: sn.pub/extras

Inhalt

Case Base Maintenance in Preference-based CBR.- Learning to Estimate: A Case-Based Approach to Task Execution Prediction .- Case-based Policy and Goal Recognition.- Adapting Sentiments with Context.- Aspect Selection for Social Recommender Systems.- Music Recommendation: Audio Neighbourhoods to Discover Music in the Long Tail.- Goal-Driven Autonomy with Semantically-annotated Hierarchical Cases.- Evaluating a Textual Adaptation System.- Visual Case Retrieval for Interpreting Skill Demonstrations.- Improving Trust-Guided Behavior Adaptation Using Operator Feedback.- Top-Down Induction of Similarity Measures Using Similarity Clouds.- Improving Case Retrieval Using Typicality.- CBR Meets Big Data: A Case Study of Large-Scale Adaptation Rule Generation.- Addressing the Cold-Start Problem in Facial Expression Recognition.- Flexible Feature Deletion: Compacting Case Bases by Selectively Compressing Case Contents.- A Case-Based Approach For Easing Schema Semantic Mapping.- Great Explanations: Opinionated Explanations for Recommendation.- Learning and Applying Adaptation Operators in Process-Oriented Case-Based Reasoning.- Fault Diagnosis via Fusion of Information from a Case Stream.- Argument-based Case Revision in CBR for Story Generation.- CBR Model for Predicting a Building's Electricity Use: On-Line Implementation in the Absence of Historical Data.- Modelling Hierarchical Relationships in Group Recommender Systems.- Semi-automatic Knowledge Extraction from Semi-structured andUnstructured Data within the OMAHA Project.- Evidence-Driven Retrieval in Textual CBR: Bridging the Gap Between Retrieval and Reuse.- Maintaining and Analyzing Production Process Definitions Using a Tree-Based Similarity Measure.- Case-Based Plan Recognition Under Imperfect Observability.