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…mehr
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.
.- 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.
.- 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.
Es gelten unsere Allgemeinen Geschäftsbedingungen: www.buecher.de/agb
Impressum
www.buecher.de ist ein Internetauftritt der buecher.de internetstores GmbH
Geschäftsführung: Monica Sawhney | Roland Kölbl | Günter Hilger
Sitz der Gesellschaft: Batheyer Straße 115 - 117, 58099 Hagen
Postanschrift: Bürgermeister-Wegele-Str. 12, 86167 Augsburg
Amtsgericht Hagen HRB 13257
Steuernummer: 321/5800/1497
USt-IdNr: DE450055826
