The topics associated to the KMi publications listed in this page were automatically generated using the CSO Classifier, a solution developed by the SKM3 team in KMi. This technology has also been adopted by Springer Nature and is used routinely by them to generate automatically the metadata for all Computer Science conference proceedings they publish.
Murgia, M., Dessi, D., Osborne, F., Buscaldi, D., Motta, E. and Recupero, D.R. (2025). CiteGen: A Web Application for Citation Recommendation Powered by LLMs and Knowledge Graphs. In: The Semantic Web: ESWC 2025 Satellite Events, 01-05 Jun 2025, Portoroz, Slovenia. https://oro.open.ac.uk/107360/.
Cadeddu, A., Chessa, A., De Leo, V., Fenu, G., Motta, E., Osborne, F., Reforgiato Recupero, D., Salatino, A. and Secchi, L. (2025). A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals. IEEE Access, 13 pp. 175271–175291. https://oro.open.ac.uk/106905/.
Aggarwal, T., Salatino, A., Osborne, F. and Motta, E. (2026). Large language models for scholarly ontology generation: An extensive analysis in the engineering field. Information Processing & Management, 63(1), https://oro.open.ac.uk/105868/.
Meloni, A., Reforgiato Recupero, D., Osborne, F., Salatino, A.A., Motta, E., Vahadati, S. and Lehmann, J. (2025). Exploring Large Language Models for Scientific Question Answering via Natural Language to SPARQL Translation. ACM Transactions on Intelligent Systems and Technology (Early access). https://oro.open.ac.uk/105679/.
Cadeddu, A., Chessa, A., De Leo, V., Fenu, G., Motta, E., Osborne, F., Recupero, D.R., Salatino, A. and Secchi, L. (2025). Benchmarking Large Language Models for Sustainable Development Goals Classification: Evaluating In-Context Learning and Fine-Tuning Strategies. In: 3rd International Workshop on Semantic Technologies and Deep Learning Models for Scientific, Technical and Legal Data (SemTech4STLD 2025), 01 Jun 2025, Portoroz, Slovenia. https://oro.open.ac.uk/105343/.
Motta, E., Daga, E., Gangemi, A., Gjelsvik, M.L., Osborne, F. and Salatino, A. (2025). The Epistemology of Fine-Grained News Classification. Semantic Web, 16(3), https://oro.open.ac.uk/104622/.
Dessí, D., Osborne, F., Buscaldi, D., Reforgiato Recupero, D. and Motta, E. (2025). CS-KG 2. 0: A Large-scale Knowledge Graph of Computer Science. Scientific Data, 12(1), https://oro.open.ac.uk/104624/.
Presutti, V., Motta, E. and Sabou, M. (2025). Opportunities for Knowledge Graphs in the AI landscape - An application-centric perspective. Journal of Web Semantics (Early access). https://oro.open.ac.uk/104426/.
Meloni, A., Recupero, D.R., Osborne, F., Salatino, A., Motta, E., Vahadati, S. and Lehmann, J. (2025). Assessing Large Language Models for SPARQL Query Generation in Scientific Question Answering. In: ISWC 2024 Special Session on Harmonising Generative AI and Semantic Web Technologies,, 13 Nov 2024, Baltimore, Maryland, USA. https://oro.open.ac.uk/104247/.
Salatino, A., Aggarwal, T., Mannocci, A., Osborne, F. and Motta, E. (2025). A survey of knowledge organization systems of research fields: Resources and challenges. Quantitative Science Studies, 6 pp. 567–610. https://oro.open.ac.uk/103702/.
Borrego, A., Dessì, D., Ayala, D., Hernández, I., Osborne, F., Recupero, D.R., Buscaldi, D., Ruiz, D. and Motta, E. (2025). Research hypothesis generation over scientific knowledge graphs. Knowledge-Based Systems, 315 https://oro.open.ac.uk/103220/.
Innominato, P., Macdonald, J., Saxton, W., Longshaw, L., Granger, R., Naja, I., Allocca, C., Edwards, R., Rasheed, S., Folkvord, F., de Batle, J., Ail, R., Motta, E., Bale, C., Fuller, C., Mullard, A., Subbe, C., Griffiths, D., Wreglesworth, N., Pecchia, L., Fico, G. and Antonini, A. (2024). Digital remote monitoring using a mobile health solution in cancer survivors: an observational pilot trial protocol. JMIR Research Protocols, 12 https://oro.open.ac.uk/102625/.
Aggarwal, T., Salatino, A., Osborne, F. and Motta, E. (2024). Identifying Semantic Relationships Between Research Topics Using Large Language Models in a Zero-Shot Learning Setting. In: 4th International Workshop on Scientific Knowledge: Representation, Discovery, and Assessment, Sci-K 2024, 12 Nov 2024, Baltimore. https://oro.open.ac.uk/101266/.
Motta, E., Osborne, F., Pulici, M.M., Salatino, A. and Naja, I. (2024). Capturing the Viewpoint Dynamics in the News Domain. In: Proceedings of the 24th International Conference on Knowledge Engineering and Knowledge Management (EKAW-24), 26-28 Nov 2024, Amsterdam, Netherlands. https://oro.open.ac.uk/100046/.
Pisu, A., Pompianu, L., Salatino, A., Osborne, F., Riboni, D., Motta, E. and Reforgiato Recupero, D. (2024). Classifying Scientific Topic Relationships with SciBERT. In: Joint Proc. of Posters, Demos, Workshops, and Tutorials of the 20th Int.l Conf. on Semantic Systems (SEMANTiCS 2024), 17-19 Sep 2024, Amsterdam. https://oro.open.ac.uk/100269/.
Pisu, A., Pompianu, L., Salatino, A., Osborne, F., Riboni, D., Motta, E. and Recupero, D.R. (2024). Leveraging Language Models for Generating Ontologies of Research Topics. In: Text2KG 2024: International Workshop on Knowledge Graph Generation from Text, 28 May 2024, Hersonissos, Crete, Greece. https://oro.open.ac.uk/99938/.
Beetz, M., Cimiano, P., Kümpel, M., Motta, E., Tiddi, I. and Töberg, J.P. (2024). Transforming Web Knowledge into Actionable Knowledge Graphs for Robot Manipulation Tasks. In: ESWC 2024 Workshops and Tutorials Joint Proceedings, 26-27 May 2024, Heraklion, Greece. https://oro.open.ac.uk/99936/.
Bolanos Burgos, F., Salatino, A., Osborne, F. and Motta, E. (2024). Artificial intelligence for literature reviews: opportunities and challenges. Artificial Intelligence Review, 57(9), https://oro.open.ac.uk/99294/.
Cadeddu, A., Chessa, A., De Leo, V., Fenu, G., Motta, E., Osborne, F., Recupero, D.R., Salatino, A. and Secchi, L. (2024). Optimizing Tourism Accommodation Offers by Integrating Language Models and Knowledge Graph Technologies. Information, 15(7), https://oro.open.ac.uk/98107/.
Lehmann, J., Meloni, A., Motta, E., Osborne, F., Recupero, D.R., Salatino, A.A. and Vahdati, S. (2024). Large Language Models for Scientific Question Answering: An Extensive Analysis of the SciQA Benchmark. In: ESWC 2024, 26-30 May 2024, Hersonissos, Greece. https://oro.open.ac.uk/98409/.
