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Research Fellow
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Dr. Angelo Salatino is a Research Fellow at the Scholarly Knowledge (SKM) group, at the Knowledge Media Institute (KMi) of the Open University. He obtained a Ph.D., studying methods for the early detection of research trends. In particular, his project aimed at identifying the emergence of new research topics at their embryonic stage (i.e., before being recognised by the research community).

He is currently working on several projects, including: i) new technologies for classifying scientific papers according to their relevant research topics, ii) automatic development of ontologies of research areas, iii) novel tools for assessing the research landscape.

Research interests

His research interests are in the areas of Semantic Web, Network Science and Knowledge Discovery technologies, with focus on the structure and evolution of science: Science of Science

External collaborations

Angelo collaborates with a number of academic and industrial partners. In particular, he collaborates with Spinger Nature, the world's largest academic book publisher, as well as universities in Cagliari (IT), Trento (IT), Universidad Carlos III de Madrid (ES), and Dresden (DE).

Keys: Semantic Web, Semantic Publishing, Data Mining, User Modelling, Knowledge Extraction, Ontologies, Scholarly Data.

Team: Tanay Aggarwal, Simone Angioni, , Enrico Motta, Francesco Osborne

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Publications

Publications | Visit External Site for Details  

Balloccu, S., Podda, A., Pompianu, L., Saia, R. and Salatino, A.A. (2024) HUMAD 2024: International Workshop on Human-Centered Modeling and Adaptation for Digital Transformation, UMAP '24: 32nd ACM Conference on User Modeling, Adaptation and Personalization, Cagliari, Italy

Publications | Visit External Site for Details  

Lehmann, J., Meloni, A., Motta, E., Osborne, F., Recupero, D., Salatino, A.A. and Vahdati, S. (2024) Large Language Models for Scientific Question Answering: An Extensive Analysis of the SciQA Benchmark, ESWC 2024, Hersonissos, Greece

Publications | Visit External Site for Details Publications | doi 

Chessa, A., Fenu, G., Motta, E., Osborne, F., Recupero, D., Salatino, A.A. and Secchi, L. (2023) Data-Driven Methodology for Knowledge Graph Generation Within the Tourism Domain, IEEE Access, 11, pp. 67567-67599, Institute of Electrical and Electronics Engineers (IEEE)

Publications | Visit External Site for Details  

Salatino, A.A., (2023) 3rd International Workshop on Scientific Knowledge Representation, Discovery, and Assessment (Sci-K 2023), WWW '23: The ACM Web Conference 2023, Austin TX USA

Publications | Visit External Site for Details Publications | doi 

Meloni, A., Angioni, S., Salatino, A.A., Osborne, F., Recupero, D. and Motta, E. (2023) Integrating Conversational Agents and Knowledge Graphs Within the Scholarly Domain, IEEE Access, 11, pp. 22468-22489, Institute of Electrical and Electronics Engineers (IEEE)

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Tech Reports

View AbstractDownload PDF

Early Detection and Forecasting of Research Trends
Techreport ID: kmi-15-02
Date: 2015
Author(s): Angelo Antonio Salatino

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Research Themes

Latest Seminar
Dr. Siān Lindley
Microsoft Research Cambridge

Actions and their Consequences: Implicit Interactions with Machine Learned Knowledge Bases

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