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Case-based reasoning research and development32nd International Conference, ICCBR 2024, Merida, Mexico, July 1-4, 2024 : proceedings /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Case-based reasoning research and developmentedited by Juan A. Recio-Garcia, Mauricio G. Orozco-del-Castillo, Derek Bridge.
其他題名:	32nd International Conference, ICCBR 2024, Merida, Mexico, July 1-4, 2024 : proceedings /
其他題名:	ICCBR 2024
其他作者:	Recio-Garcia, Juan A.
團體作者:
出版者:	Cham :Springer Nature Switzerland :2024.
面頁冊數:	xiii, 462 p. :ill. (chiefly col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Case-based reasoningCongresses.
電子資源:	https://doi.org/10.1007/978-3-031-63646-2
ISBN:	9783031636462$q(electronic bk.)

Case-based reasoning research and development32nd International Conference, ICCBR 2024, Merida, Mexico, July 1-4, 2024 : proceedings /
Case-based reasoning research and development32nd International Conference, ICCBR 2024, Merida, Mexico, July 1-4, 2024 : proceedings /[electronic resource] :ICCBR 2024edited by Juan A. Recio-Garcia, Mauricio G. Orozco-del-Castillo, Derek Bridge. - Cham :Springer Nature Switzerland :2024. - xiii, 462 p. :ill. (chiefly col.), digital ;24 cm. - Lecture notes in computer science,147751611-3349 ;. - Lecture notes in computer science ;4891..

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.

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.

ISBN: 9783031636462$q(electronic bk.)

Standard No.: 10.1007/978-3-031-63646-2doiSubjects--Topical Terms:

442664
Case-based reasoning
--Congresses.

LC Class. No.: Q338.8 / .I58 2024

Dewey Class. No.: 006.333

Case-based reasoning research and development32nd International Conference, ICCBR 2024, Merida, Mexico, July 1-4, 2024 : proceedings /
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