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.
On 16th May 2017, the STEM Faculty of my university organised a 3 Minutes Thesis (3MT) in which each candidate has a time slot of three minutes to describe their thesis. The speech can be supported by one static slide showing important features of the work. I wish I had shown the one above. In […]
“How are topics born? Understanding the research dynamics preceding the emergence of new areas” is a peer-reviewed paper submitted to PeerJ Computer Science. The paper has been submitted in July 2016 and accepted in May 2017. All the co-authors are thankful to the reviewers and the editor for providing insightful comments and thus improving the […]