Case-Based Reasoning Research and Development [electronic resource] : 31st International Conference, ICCBR 2023, Aberdeen, UK, July 17-20, 2023, Proceedings / edited by Stewart Massie, Sutanu Chakraborti.

Colaborador(es): Massie, Stewart [editor.] | Chakraborti, Sutanu [editor.] | SpringerLink (Online service)Tipo de material: TextoTextoSeries Lecture Notes in Artificial Intelligence ; 14141Editor: Cham : Springer Nature Switzerland : Imprint: Springer, 2023Edición: 1st ed. 2023Descripción: XI, 426 p. 131 illus., 96 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783031401770Tema(s): Artificial intelligence | Information technology -- Management | Computer engineering | Computer networks  | Artificial Intelligence | Computer Application in Administrative Data Processing | Computer Engineering and NetworksFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 006.3 Clasificación LoC:Q334-342TA347.A78Recursos en línea: Libro electrónicoTexto
Contenidos:
CBR and Deep Learning -- Examining the Impact of Network Architecture on Extracted Feature Quality for CBR -- Synergies between Case-based Reasoning and Deep Learning for Survival Analysis in Oncology -- CBR Assisted Context-Aware Surface Realisation for Data-to-Text Generation -- Representation and Similarity -- Explanation of Similarities in Process-Oriented Case-Based Reasoning by Visualization -- On-demand and model-driven case building based on distributed data sources -- The Case for Circularities in Case-Based Reasoning -- A Contextual Information-augmented Probabilistic Case-based Reasoning Model for Knowledge Graph Reasoning -- Case-based Sample Generation using Multi-Armed Bandits -- Hybrid Event Memory as a Case Base for State Estimation in Cognitive Agents -- CBR and Explainable AI Cases are King: A User Study of Case Presentation to Explain CBR Decisions -- CBR driven Interactive Explainable AI -- Selecting Explanation Methods for Intelligent IoT Systems: a Case-Based Reasoning Approach -- Case Based Explanation for Time Series Forecasting Models -- Case Base Maintenance -- Group Fairness in Case-Based Reasoning -- Addressing Underestimation Bias in CBR through Case-Base Maintenance -- The Problem Drift Problem and First Steps Towards Addressing It -- Adaptation: Techniques and Application Case-Based Adaptation of Argument Graphs with WordNet and Large Language Models -- Failure-Driven Transformational Case Reuse of Explanation Strategies in CloodCBR -- A Case-Based Approach for Workflow Flexibility by Deviation -- Lazy Adaptation Knowledge Learning based on Frequent Closed Itemsets -- Case-Based Applications -- An Overview and Comparison of Case-Based Reasoning Frameworks -- Case-Based Cleaning of Text Images -- A Multi-agent Case-based Reasoning Intrusion Detection System Prototype -- A Case-Based Reasoning Approach to Company Sector Classification Using a Novel Time-Series Case Representation -- An Integrated Approach to Predicting the Influence of Reputation Mechanisms on Q&A Communities -- Retrieval of similar cases to improve the diagnosis of diabetic retinopathy.
En: Springer Nature eBookResumen: This book constitutes the proceedings of the 31st International Conference on Case-Based Reasoning Research and Development, ICCBR 2023, which took place in Aberdeen, UK, in July 2023. The 26 full papers included in this book were carefully reviewed and selected from 79 submissions. The papers have been organized in topical sections as follows: CBR and deep learning; representation and similarity; CBR and explainable AI; case base maintenance; adaptation: techniques and application; and case-based applications.
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Acceso multiusuario

CBR and Deep Learning -- Examining the Impact of Network Architecture on Extracted Feature Quality for CBR -- Synergies between Case-based Reasoning and Deep Learning for Survival Analysis in Oncology -- CBR Assisted Context-Aware Surface Realisation for Data-to-Text Generation -- Representation and Similarity -- Explanation of Similarities in Process-Oriented Case-Based Reasoning by Visualization -- On-demand and model-driven case building based on distributed data sources -- The Case for Circularities in Case-Based Reasoning -- A Contextual Information-augmented Probabilistic Case-based Reasoning Model for Knowledge Graph Reasoning -- Case-based Sample Generation using Multi-Armed Bandits -- Hybrid Event Memory as a Case Base for State Estimation in Cognitive Agents -- CBR and Explainable AI Cases are King: A User Study of Case Presentation to Explain CBR Decisions -- CBR driven Interactive Explainable AI -- Selecting Explanation Methods for Intelligent IoT Systems: a Case-Based Reasoning Approach -- Case Based Explanation for Time Series Forecasting Models -- Case Base Maintenance -- Group Fairness in Case-Based Reasoning -- Addressing Underestimation Bias in CBR through Case-Base Maintenance -- The Problem Drift Problem and First Steps Towards Addressing It -- Adaptation: Techniques and Application Case-Based Adaptation of Argument Graphs with WordNet and Large Language Models -- Failure-Driven Transformational Case Reuse of Explanation Strategies in CloodCBR -- A Case-Based Approach for Workflow Flexibility by Deviation -- Lazy Adaptation Knowledge Learning based on Frequent Closed Itemsets -- Case-Based Applications -- An Overview and Comparison of Case-Based Reasoning Frameworks -- Case-Based Cleaning of Text Images -- A Multi-agent Case-based Reasoning Intrusion Detection System Prototype -- A Case-Based Reasoning Approach to Company Sector Classification Using a Novel Time-Series Case Representation -- An Integrated Approach to Predicting the Influence of Reputation Mechanisms on Q&A Communities -- Retrieval of similar cases to improve the diagnosis of diabetic retinopathy.

This book constitutes the proceedings of the 31st International Conference on Case-Based Reasoning Research and Development, ICCBR 2023, which took place in Aberdeen, UK, in July 2023. The 26 full papers included in this book were carefully reviewed and selected from 79 submissions. The papers have been organized in topical sections as follows: CBR and deep learning; representation and similarity; CBR and explainable AI; case base maintenance; adaptation: techniques and application; and case-based applications.

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