Vor Ort
Merkzettel Warenkorb
Produktbild: Case-Based Reasoning Research and Development
Band 15662 - 16%

Case-Based Reasoning Research and Development 33rd International Conference, ICCBR 2025, Biarritz, France, June 30–July 3, 2025, Proceedings

Aus der Reihe Lecture Notes in Computer Science
16% sparen

127,99 € UVP 153,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

30.06.2025

Abbildungen

XIX, 122 illus., 91 illus. in color., farbige Illustrationen, schwarz-weiss Illustrationen

Herausgeber

Isabelle Bichindaritz + weitere

Verlag

Springer

Seitenzahl

486

Maße (L/B/H)

23,5/15,5/2,8 cm

Gewicht

762 g

Sprache

Englisch

ISBN

978-3-031-96558-6

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

30.06.2025

Abbildungen

XIX, 122 illus., 91 illus. in color., farbige Illustrationen, schwarz-weiss Illustrationen

Herausgeber

Verlag

Springer

Seitenzahl

486

Maße (L/B/H)

23,5/15,5/2,8 cm

Gewicht

762 g

Sprache

Englisch

ISBN

978-3-031-96558-6

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

Noch keine Bewertungen vorhanden

Verfassen Sie die erste Bewertung zu diesem Artikel

Helfen Sie anderen Kundinnen und Kunden durch Ihre Meinung.

Kundinnen und Kunden meinen

Bewertungen (0)
  • Produktbild: Case-Based Reasoning Research and Development

  • .- 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.