Abstract
We present PolyNarrative, a new multilingual dataset of news articles, annotated for narratives. Narratives are overt or implicit claims, recurring across articles and languages, promoting a specific interpretation or viewpoint on an ongoing topic, often propagating mis/disinformation. We developed two-level taxonomies with coarse- and fine-grained narrative labels for two domains: (i) climate change and (ii) the military conflict between Ukraine and Russia. We collected news articles in four languages (Bulgarian, English, Portuguese, and Russian) related to the two domains and manually annotated them at the paragraph level. We make the dataset publicly available, along with experimental results of several strong baselines that assign narrative labels to news articles at the paragraph or the document level. We believe that this dataset will foster research in narrative detection and enable new research directions towards more multi-domain and highly granular narrative related tasks.

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This work introduces a web application for extracting, processing, and visualizing data from sleep studies reports. Using Optical Character Recognition (OCR) and Natural Language Processing (NLP), the pipeline extracts over 75 key data points from four types of sleep reports. The web application offers an intuitive interface to view individual reports' details and aggregate data from multiple reports. The pipeline demonstrated 100% accuracy in extracting targeted information from a test set of 40 reports, even in cases with missing data or formatting inconsistencies. The developed tool streamlines the analysis of OSA reports, reducing the need for technical expertise and enabling healthcare providers and researchers to utilize sleep study data efficiently. Future work aims to expand the dataset for more complex analyses and imputation techniques.

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This chapter examines how GenAI and predictive modelling strategies affect hyperpersonalised marketing. Through a comprehensive literature review and case studies, it examines hyper-p ersonalisation's theoretical frameworks, technical infrastructures, and ethical and governance issues. Large language models, generative adversarial networks, and diffusion models combined with advanced predictive analytics allow firms to scale real- time, highly individualised customer experiences. Effective implementation requires sophisticated data architectures, algorithmic transparency, and strong privacy protections. Integration complexity and ethical accountability are major barriers to consumer engagement and conversion, according to the research. Based on these findings, the chapter proposes an integrated framework that combines technological innovation with ethics and customer focus. This research advances marketing theory and provides practical advice for companies using AI- driven hyper-personalisation while maintaining consumer trust and regulatory compliance. © 2026, IGI Global Scientific Publishing. All rights reserved.

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The Informatics Engineering degree at ISEP, aligned with international standards, was the first undergraduate degree in Portugal to be certified with EUR-ACE®. The programme emphasizes project-based learning, in which students, working in teams, develop interdisciplinary projects applying knowledge from all courses in each semester. A specific laboratory-project course coordinates an integrative project that aims to address complex problems. In the 2nd semester, two computer engineering courses (object-oriented programming and software engineering), and two mathematics courses (discrete mathematics and statistics) are involved, besides the laboratory/project course. This paper focuses on the integration of mathematics with informatics courses in this project, addressing real-world-like problems, bridging software engineering with mathematical topics. To assess the adopted PBL, enquiries were carried out among students. This approach fosters active learning and reinforces the relevance of mathematics within engineering, preparing students for job market demands. © 2026, IGI Global Scientific Publishing. All rights reserved.

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