Case-Based Reasoning Research and Development

33rd International Conference, ICCBR 2025, Biarritz, France, June 30-July 3, 2025, Proceedings
Herausgegeben:Bichindaritz, Isabelle; López, Beatriz

• Broschiertes Buch

Produktbeschreibung

This book constitutes the refereed proceedings of the 33rd International Conference on Case-Based Reasoning Research and Development, ICCBR 2025, held in Biarritz, France, during June 30 July 3, 2025.

The 30 full papers presented in this volume were carefully reviewed and selected from 81 submissions. The book also contains one invited talk in full-paper lenght. The papers are grouped into the following topical sections: Invited Talk; CBR and Generative AI Synergies; Theoretical or Methodological CBR Research; and Applied CBR Research.

Produktdetails

• Lecture Notes in Computer Science 15662
• Verlag: Springer / Springer Nature Switzerland / Springer, Berlin
• Artikelnr. des Verlages: 978-3-031-96558-6
• Seitenzahl: 508
• Erscheinungstermin: 30. Juni 2025
• Englisch
• Abmessung: 235mm x 155mm x 28mm
• Gewicht: 762g
• ISBN-13: 9783031965586
• ISBN-10: 3031965582
• Artikelnr.: 74214814

Inhaltsangabe

.- Invited Talk.

.- EXAR: A Unified Experience-Grounded Agentic Reasoning Architecture.

.- CBR and Generative AI Synergies.

.- AlignLLM: Alignment-based Evaluation using Ensemble of LLMs-as-Judges for Q&A.

.- Visual Question Answering to Generate Case-Based Explanations for Image Classification.

.- Integrating Case-Based Reasoning with LLM for Expense Fraud Detection.

.- LLM-Driven Case-Base Populating for Structuring and Integrating Restoration Experiences.

.- Explaining Translational Embedding Models in Recommender Systems Using Knowledge Graphs and Language Models.

.- Fuzzy Symbolic Reasoning for few-shot KBQA: A CBR-inspired Generative Approach.

.- Context Driven Multi-Query Resolution using LLM-RAG to support the Revision of Explainability needs.

.- LLsiM: Large Language Models for Similarity Assessment in Case-Based Reasoning.

.- Offline-to-Online: Case-Based Knowledge Distillation with Large Language Models for Reinforcement Learning.

.- Utilizing the Structure of Process Models for Guided Generation of Explanatory Texts.

.- Case-Based Reasoning in Generative Agents: Review and Prospect.

.- Theoretical or Methodological CBR Research.

.- Evaluating Objective Metrics for Time Series Model Explainability.

.- A Knowledge Representation Approach for Reasoning with Adaptation Rules.

.- Efficient Case Retrieval Using Dropout Similarity Highway Multigraphs.

.- Advanced Search Techniques for Determining Optimal Sequences of Adaptation Rules in Process-Oriented Case-Based Reasoning.

.- A Framework for Supporting the Iterative Design of CBR Applications.

.- Two-Agent Case-Based Reasoning for Prediction.

.- Towards Non-Programmed Robotic Manipulation of Novel Tasks using GA-driven CBR.

.- Fast Locality Sensitive Hashing with Theoretical Guarantee.

.- Learning CaseØstrem Features with Proxy-Guided Deep Neural Networks.

.- Integration of Time Series Embedding for Efficient Retrieval in Case-Based Reasoning.

.- Extracting Features with Deep Learning for Ensemble-Driven Case-Based Classification.

.- Applied CBR Research.

.- CBRinR Multitask Multiomics Case-based Reasoning in Bioinformatics.

.- Case-based Causal Reasoning for Elite Sport Training.

.- Representing expert reasoning experience by process cases Application to the delimitation of mobile genetic elements in bacterial chromosomes.

.- Clinical Decision Support for Skin Tumor Treatment: A Case-Based Reasoning Approach.

.- Analysing the contribution of sequential patterns in CBR for childhood obesity prediction.

.- Case-Based Activity Detection from Segmented Internet of Things Data.

.- Explainable sleep-wake recognition using a twin XCBR system with prototypes to improve retrieval efficiency.

.- Case-Based Reasoning with Diffusion Model for Ransomware Detection.