Supporting Editorial Activities at Springer Nature

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.

Thanapalasingam, T., Osborne, F., Birukou, A. and Motta, E. (2018) Ontology-Based Recommendation of Editorial Products, The International Semantic Web Conference 2018, Monterey, California, USA

Osborne, F. and Motta, E. (2018) Pragmatic Ontology Evolution: Reconciling User Requirements and Application Performance, International Semantic Web Conference 2018, Monterey, California, USA

Salatino, A.A., Thanapalasingam, T., Mannocci, A., Osborne, F. and Motta, E. (2018) The Computer Science Ontology: A Large-Scale Taxonomy of Research Areas, The International Semantic Web Conference 2018, Monterey, California, USA