Case-Based Reasoning Research and Development
Description
This book constitutes the refereed proceedings of the 32nd International Conference on Case-Based Reasoning Research and Development, ICCBR 2024, held in Merida, Mexico, during July 1-4, 2024.
The 29 full papers included in this book were carefully reviewed and selected from 91 submissions. They cover a wide range of CBR topics of interest both to practitioners and researchers, including: improvements to the CBR methodology itself: case representation, similarity, retrieval, adaptation, etc.; synergies with other Artificial Intelligence topics, such as Explainable AI and Large Language Models; and finally a whole catalog of applications to different domains such as health-care, education, and legislation.
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Content
.- Integrating kNN Retrieval with Inference on Graphical Models in Case-Based Reasoning.
.- Updating Global Similarity Measures in Learning CBR Systems.
.- Even-Ifs From If-Onlys: Are the Best Semi-Factual Explanations Found Using Counterfactuals As Guides?.
.- Improving Complex Adaptations in Process-Oriented Case-Based Reasoning by Applying Rule-Based Adaptation.
.- Visualization of similarity models for CBR comprehension and maintenance.
.- Use Case-Specific Reuse of XAI Strategies: Design and Analysis Through An Evaluation Metrics Library.
.- An Empirical Analysis of User Preferences Regarding XAI metrics.
.- CBR-Ren: A Case-Based Reasoning Driven Retriever-Generator Model for Hybrid Long-form Numerical Reasoning.
.- A Case-based Reasoning and Explaining Model for Temporal Point Process.
.- Extracting Indexing Features for CBR from Deep Neural Networks: A Transfer Learning Approach.
.- Ensemble Stacking Case-Based Reasoning for Regression.
.- Retrieval Augmented Generation with LLMs for Explaining Business Process Models.
.- The Intelligent Tutoring System AI-VT with Case-Based Reasoning and Real Time Recommender Models.
.- Explaining Multiple Instances Counterfactually: User Tests of Group-Counterfactuals for XAI.
.- Olaaaf: a General Adaptation Prototype.
.- Identifying Missing Sensor Values in IoT Time Series Data: A Weight-Based Extension of Similarity Measures for Smart Manufacturing.
.- Examining the potential of sequence patterns from EEG data as alternative case representation for seizure detection.
.- Towards a Case-Based Support for Responding Emergency Calls.
.- CBRkit: An Intuitive Case-Based Reasoning Toolkit for Python.
.- Experiential questioning for VQA.
.- Autocompletion of Architectural Spatial Configurations using Case-Based Reasoning, Graph Clustering, and Deep Learning.
.- A Case-Based Reasoning Approach to Post-Injury Training.
.- Towards Network Implementation of CBR: Case Study of a Neural Network K-NN Algorithm.
.- Aligning to Human Decision-Makers in Military Medical Triage.
.- Counterfactual-Based Synthetic Case Generation.
.- On Implementing Case-Based Reasoning with Large Language Models.
.- Using Case-Based Causal Reasoning to Provide Explainable Counterfactual Diagnosis in Personalized Sprint Training.
.- Item-Specific Similarity Assessments for Explainable Depression Screening.
.- CBR-RAG: Case-Based Reasoning for Retrieval Augmented Generation in LLMs for Legal Question Answering.