Titlebook: Intelligent Data Engineering and Automated Learning – IDEAL 2024; 25th International C Vicente Julian,David Camacho,Antonio Tallón-Balles C

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Association Rules Mining with Auto-encodersle classification systems. Classical association rule mining algorithms have several limitations, especially with regards to their high execution times and number of rules produced. Over the past decade, neural network solutions have been used to solve various optimization problems, such as classifi

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Using Contrastive Learning to Map Stylistic Similarities in Narrative Writersally by experts. This research field, intertextuality, seeks to understand how writers relate to each other and how the works of one writer have reflected on the work of another. This analysis usually provides insight into the historical, cultural, biographical, and literary contexts that shape lite

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Automatic Classification of Signal and Noise in Functional Magnetic Resonance Imaging Scans Using Coonance imaging (fMRI) data has significantly advanced our understanding of brain functionality and the diagnosis of neurological disorders. This paper explores the application of Convolutional Neural Networks (CNNs) to enhance the accuracy and efficiency of fMRI data analysis, addressing challenges

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How Resilient are Language Models to Text Perturbations?h between their training environments and real-world applications. This study evaluates the resilience of four prominent models in five different NLP tasks when confronted with perturbed inputs. We investigate three categories of perturbations: character-level, word-level and miscellaneous perturbat

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