by Natalia Ostapuk, Ljiljana Dolamic, Alain Mermoud, Philippe Cudré-Mauroux | May 31, 2024 | Publications, Scientific Articles
Abstract: Extreme multi-label (XML) classification involves assigning multiple labels to an instance from an extremely largeset of possible labels. Despite its significance, zero-shot learning within the context of XML classification remains relatively understudied....
by Natalia Ostapuk, Julien Audiffren, Ljiljana Dolamic, Alain Mermoud, Philippe Cudré-Mauroux | May 13, 2024 | Podcasts, Publications, Scientific Articles
Abstract: Extreme Multi Label (XML) problems, and in particular XML completion — the task of prediction the missing labels of an entity — have attracted significant attention in the past few years. Most XML completion problems can organically leverage a...
by Ljiljana Dolamic, Julian Jang-Jaccard, Alain Mermoud, Vincent Lenders | Apr 23, 2024 | Publications, Scientific Articles
Abstract: Identifying emerging technologies and forecasting their trends is pivotal for stakeholders and decision-makers across academia, industry, and government agencies. The current strategies employed to track technology trends often rely on proprietary closed...
by André Charneca, Angelika Romanou, Ljiljana Dolamic, Alain Mermoud | Dec 22, 2023 | Podcasts
Abstract This study investigates the effectiveness of two distinct computational approaches for mapping the technological landscape by extracting company and product relations from news articles. The first approach leverages Large Language Models (LLMs), specifically...
by Michael Tsesmelis, Ljiljana Dolamic, Marcus Matthias Keupp, Dimitri Percia David, Alain Mermoud | Sep 20, 2023 | Publications, Scientific Articles
Abstract The need for dependable and real-time insights on technological paradigm shifts requires objective information. We develop a lean recommender system which predicts emerging technology by a sequential blend of machine learning and network analytics. We...
