Great news for our team! A paper authored by Angelo A. Salatino, Francesco Osborne and Enrico Motta, published last June to PeerJ Computer Science journal, was one of the top 5 most viewed in the areas of Artificial Intelligence, Data Science and Digital Libraries. The paper entitled “How are topics born? Understanding the research dynamics preceding the emergence of new areas” is a […]
Forecasting the Spreading of Technologies in Research Communities @ K-CAP 2017 from Francesco Osborne
On the 29th November 2017, Angelo, Andrea and Thiviyan attended the second edition of SpringerNature HackDay in London (@ SpringerNature Campus). Aliaksandr Birukou, Executive Editor of Computer Science at Springer Nature and collaborator of our research team at the Knowledge Media Institute, also joined our group on the HackDay. The whole event aimed at joining together the […]
On the 29th November 2017, the SKM3 team attended the second edition of SpringerNature HackDay in London (@ SpringerNature Campus). Aliaksandr Birukou, Executive Editor of Computer Science at Springer Nature and collaborator of our research team at the Knowledge Media Institute, also joined Andrea, Thiviyan and Angelo on the HackDay. The whole event aimed at joining together the […]
Supporting Springer Nature Editors by means of Semantic Technologies from Francesco Osborne
“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 […]
On the 8th February, Angelo delivered a seminar to the KMi in which he described the work he has been doing in the last two years for his postgraduate research. He started with a little bit of introduction about science. Shortly, he moved to the currently available technologies for keeping track of the development of the different […]
Klink-2 is an application which takes as input large amounts of scholarly metadata and automatically generates an OWL ontology containing all the research areas mined from the input data and their semantic relationships. It was developed to produced large scale ontology of research topics. The traditional way to address the problem of identifying and […]
Techminer Architecture. TechMiner is a novel approach, which combines natural language processing, machine learning and semantic technologies, for mining technologies from research publications and generating an OWL ontology describing their relationships with other research entities. The resulting knowledge base can support tasks such as: richer semantic search, richer expert search, monitoring the emergence and impact […]
Smart Topic Miner (STM) is a web application which uses Semantic Web technologies to classify scholarly publications on the basis of Computer Science Ontology (CSO), a very large automatically generated ontology of research areas. STM was developed to support the Springer Nature Computer Science editorial team in classifying proceedings in the LNCS family. It analyses […]
Scholarly Knowledge Mining
Digital Humanities
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