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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.
List of contents
.- 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.
