supporting editorial activities at springer nature project full details
Senior Research Fellow
Timeline:01 May 2018 - 31 Jan 2021
Supporting Editorial Activities at Springer Nature
The project aims at fostering Springer Nature editorial activities by supporting them with a variety of smart solutions leveraging artificial intelligence, data mining, and semantic technologies. In particular, the KMi team will support Springer Nature editorial team in classifying proceedings and other editorial products, taking informed decisions about their marketing strategy, and improve their internal classification.
The main objectives of the project are:
- Producing several analytics solutions for the analysis of big scholarly data.
- Automatically generating a large-scale ontology describing research topics in the field of Engineering.
- Enhancing the Smart Topics Miner, a tool developed to support the Springer Nature editorial team in classifying proceedings.
- Releasing the Computer Science Ontology, the largest ontology of research areas in the field of Computer Science, which currently includes about 15K topics and 70K semantic relationships.
01 Sep 2022
23 Feb 2021
10 Jan 2019
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)
Peng, C., Xia, F., Naseriparsa, M. and Osborne, F. (2023) Knowledge Graphs: Opportunities and Challenges, Artificial Intelligence Review, pp. (Early Access)
Angioni, S., Salatino, A.A., Osborne, F., Birukou, A., Recupero, D. and Motta, E. (2022) Leveraging Knowledge Graph Technologies to Assess Journals and Conferences at Springer Nature, 21st International Semantic Web Conference, ISWC 2022, Hangzhou, China
Angioni, S., Salatino, A.A., Osborne, F., Recupero, D. and Motta, E. (2022) The AIDA Dashboard: a Web Application for Assessing and Comparing Scientific Conferences, IEEE Access, pp. (In press)
Chessa, A., Fenu, G., Motta, E., Recupero, D., Osborne, F., Salatino, A.A. and Secchi, L. (2022) Enriching Data Lakes with Knowledge Graphs, Knowledge Graph Generation from Text Workshop, Creete, Greece