Classifying research papers according to their research topics is an important task to improve their retrievability, assist the creation of smart analytics, and support a variety of approaches for analysing and making sense of the research environment. In this repository, we present the CSO Classifier, a new unsupervised approach for automatically classifying research papers according to...
Congratulations to Angelo Salatino for succeeding in his viva! On 31st May 2019, Angelo Salatino successfully defended his PhD thesis on Early Detection of Research Trends. The thesis is a body of research work over the last three years leading to a successful system that identifies the emergence of new research topics up to two years before they emerge (i.e., at their embryonic stage). The work...
We are pleased to announce that we recently created a new release of the CSO Classifier (v2.1), an application for automatically classifying research papers according to the Computer Science Ontology (CSO). Recently, we have been intensively working on improving its scalability, removing all its bottlenecks and making sure it could be run on large corpus. Specifically, in this version we...
The Knowledge Media Institute (KMi) of The Open University and Springer Nature are partnering to provide a comprehensive Computer Science Ontology (CSO) to a broad range of communities engaged with scholarly data. CSO can be accessed free of charge through the CSO Portal, a web application that enables users to download, explore, and provide feedback on the ontology. Ontologies of research...