Case-Based Reasoning Research and Development (eBook, PDF)
32nd International Conference, ICCBR 2024, Merida, Mexico, July 1-4, 2024, Proceedings
Redaktion: Recio-Garcia, Juan A.; Bridge, Derek; Orozco-del-Castillo, Mauricio G.
Alle Infos zum eBook verschenken
Case-Based Reasoning Research and Development (eBook, PDF)
32nd International Conference, ICCBR 2024, Merida, Mexico, July 1-4, 2024, Proceedings
Redaktion: Recio-Garcia, Juan A.; Bridge, Derek; Orozco-del-Castillo, Mauricio G.
- Format: PDF
- Merkliste
- Auf die Merkliste
- Bewerten Bewerten
- Teilen
- Produkt teilen
- Produkterinnerung
- Produkterinnerung
Hier können Sie sich einloggen
Bitte loggen Sie sich zunächst in Ihr Kundenkonto ein oder registrieren Sie sich bei bücher.de, um das eBook-Abo tolino select nutzen zu können.
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
- Geräte: PC
- ohne Kopierschutz
- eBook Hilfe
- Größe: 33.11MB
- Case-Based Reasoning Research and Development (eBook, PDF)61,95 €
- Case-Based Reasoning Research and Development (eBook, PDF)73,95 €
- Case-Based Reasoning Research and Development (eBook, PDF)40,95 €
- Case-Based Reasoning Research and Development (eBook, PDF)65,95 €
- Advances in Case-Based Reasoning (eBook, PDF)73,95 €
- Case-Based Reasoning Research and Development (eBook, PDF)73,95 €
- Case-Based Reasoning Research and Development (eBook, PDF)40,95 €
-
-
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.
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.
- Produktdetails
- Verlag: Springer International Publishing
- Seitenzahl: 462
- Erscheinungstermin: 23. Juni 2024
- Englisch
- ISBN-13: 9783031636462
- Artikelnr.: 72241058
- Verlag: Springer International Publishing
- Seitenzahl: 462
- Erscheinungstermin: 23. Juni 2024
- Englisch
- ISBN-13: 9783031636462
- Artikelnr.: 72241058
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
.- 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.
.- 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.