New release: CSO Classifier v2.1

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. […]

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CSO Classifier

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 page, we present the CSO Classifier, a new unsupervised approach for automatically classifying research papers according […]

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Computer Science Ontology

The Computer Science Ontology is a large-scale ontology of research areas that was automatically generated using the Klink-2 algorithm [1] on a dataset of about 16 million publications, mainly in the field of Computer Science. In the rest of the paper, we will refer to this corpus as the Rexplore dataset [2]. The current version of CSO […]

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Classifying Research Papers with the Computer Science Ontology

“Classifying Research Papers with the Computer Science Ontology” is a demo paper submitted to the International Semantic Web Conference (ISWC) 2018 , 8-12 October 2018, Monterey, California, USA, 2018. Poster DOI. 10.21954/ou.rd.7204814 Poster paper PDF. http://oro.open.ac.uk/55908/ Code: Authors. Angelo A. Salatino, Thiviyan Thanapalasingam, Andrea Mannocci, Francesco Osborne, Enrico Motta Abstract. Ontologies of research areas are important tools for characterising, exploring […]

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