Foundations of Intelligent Systems (eBook, PDF)

27th International Symposium, ISMIS 2024, Poitiers, France, June 17-19, 2024, Proceedings
Redaktion: Appice, Annalisa; Ras, Zbigniew; Hadjali, Allel; Hacid, Mohand-Said; Azzag, Hanane

• Format: PDF

Produktbeschreibung

This book constitutes the proceedings of the 27th International Symposium on Methodologies for Intelligent Systems, ISMIS 2024, held in Poitiers, France, in June 2024.

The 18 full papers, 6 short papers and 5 industrial papers presented in this volume were carefully reviewed and selected from 46 submissions. The papers are organized in the following topical sections: Classification and Clustering; Neural Network and Natural Language Processing; AI tools and Models; Neural Network and Data Mining; Explainability in AI; Industry Session; Learning with Complex Data; Recommendation Systems and Prediction.

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 316
• Erscheinungstermin: 16. Juni 2024
• Englisch
• ISBN-13: 9783031627002
• Artikelnr.: 72242980

Inhaltsangabe

.- Classification and Clustering.

.- Improving the robustness to color perturbations of classification and regression models in the visual evaluation of fruits and vegetables.

.- Clustering Under Radius Constraints Using Minimum Dominating Sets.

.- Learning Typicality Inclusions in a Probabilistic Description Logic for Concept Combination.

.- Neural Network and Natural Language Processing.

.- LLMental Classification of mental disorders with large language models.

.- CSEPrompts A Benchmark of Introductory Computer Science Prompts.

.- Semantically-Informed Domain Adaptation for Named Entity Recognition.

.- Token Pruning by Dimensionality Reduction Methods on TCT Colbert for Reranking.

.- AI Tools and Models.

.- Exploiting microRNA expression data for the diagnosis of disease conditions and the discovery of novel biomarkers.

.- HERSE: Handling and Enhancing RDF Summarization through blank node Elimination.

.- Rough Sets For a Neuromorphic CMOS System.

.- Neural Network and Data Mining.

.- Erasing the Shadow Sanitization of Images with Malicious Payloads using Deep Autoencoders.

.- Digilog Enhancing Website Embedding on Local Governments - A Comparative Analysis.

.- A Stream Data Mining Approach to Handle Concept Drifts in Process Discovery.

.- Explainability in AI.

.- Enhancing temporal Transformers for financial time series via local surrogate interpretability.

.- Explaining commonalities of clusters of RDF resources in natural language.

.- Shapley-Based Data Valuation Method for the Machine Learning Data Markets (MLDM).

.- Industry Session.

.- ScoredKNN: An Efficient KNN Recommender based on Dimensionality Reduction for Big Data.

.- Siamese Networks for Unsupervised Failure Detection in Smart Industry.

.- Adaptive Forecasting of Extreme Electricity Load.

.- Explaining Voltage Control Decisions: A Scenario-Based Approach in Deep Reinforcement Learning.

.- Knowledge Graphs for Data Integration in Retail.

.- Learning with Complex Data.

.- Bayesian Approach for Parameter Estimation in Vehicle Lateral Dynamics.

.- Assessing Distance Measures for Change Point Detection in Continual Learning Scenarios.

.- SPLindex A Spatial Polygon Learned Index .

.- Recommendation Systems and Prediction.

.- Action Rules Discovery Leveraging Attributes Correlation Based Vertical Partitioning.

.- HalpernSGD A Halpern-inspired Optimizer for Accelerated Neural Network Convergence and Reduced Carbon Footprint.

.- Integrating Predictive Process Monitoring Techniques in Smart Agriculture.