Smart Topic Miner Smart Topic Miner (STM) is an application that assists the Springer Nature editorial team in classifying the scientific literature in Computer Science in terms of a catalogue of about 15K research topics, with a very high degree of accuracy. This catalogue was itself generated by our team using a highly innovative knowledge […]
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 […]
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 […]
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. […]
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 […]
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 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 […]
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, […]
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 […]
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 […]
Scholarly Knowledge Mining
Digital Humanities
Data Science
Smart Cities and Robotics
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