  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 paper, we present the CSO Classifier, a
new unsupervised approach for automatically classifying research papers
according to the Computer Science Ontology (CSO), a comprehensive ontology of
re-search areas in the field of Computer Science. The CSO Classifier takes as
input the metadata associated with a research paper (title, abstract, keywords)
and returns a selection of research concepts drawn from the ontology. The
approach was evaluated on a gold standard of manually annotated articles
yielding a significant improvement over alternative methods.
