Tag Archives: skm3

The CSO Classifier nominated for the Best Paper Award

Last week, Angelo was in Oslo for the 23rd edition of the International Conference on Theory and Practice of Digital Libraries (TPDL2019). Every year, this conference attracts many researchers from all over the world, working in the fields of digital libraries, information retrieval, text analysis, web archives, and many others. Angelo attended the conference to present […]

CSO-Classifier available on PIP

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 […]

Angelo succeeds in his VIVA

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 […]

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. […]

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 […]

The CSO Classifier: Ontology-Driven Detection of Research Topics in Scholarly Articles

Abstract. 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 […]

The Open University and Springer Nature launch the Computer Science Ontology

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 […]

SKM3 at ISWC 2018

Every year the International Semantic Web Conference (ISWC) is the main destination for many researchers in the Semantic Web community. The 17th edition of the conference was held last week at the Asilomar Conference Grounds in Monterey, California, and it hosted around 500 researchers coming from all around the world.This year the SKM3 presented three full papers, covering all the main tracks, […]

AUGUR presented at JCDL 2018

The ACM/IEEE Joint Conference on Digital Libraries in 2018 (JCDL 2018) took place last week in Fort Worth (Texas). Angelo attended the conference to discuss his recent advances showed in the research paper “AUGUR: Forecasting the Emergence of New Research Topics”. In brief, Augur is a framework analysing the diachronic relationships between research areas and […]

Great success for the SKM3 team at ISWC 2018

The SKM3 team, the KMi research group on scholarly analytics, will present three full papers at the 2018 International Semantic Web Conference (ISWC), the premiere international venue for the Semantic Web and Linked Data communities, which will be held in October in Monterey, California. The SKM3 team succeeded in having a paper accepted in each […]