Tag Archives: Automatic Topic Classification

Smart Topic Miner

Smart Topic Miner (STM) is a web application which uses Semantic Web technologies to classify scholarly publications on the basis of Computer Science Ontology (CSO), a very large automatically generated ontology of research areas. STM was developed to support the Springer Nature Computer Science editorial team in classifying proceedings in the LNCS family. It analyses […]

The Rexplore team and Springer Nature launch a new collaboration

The Rexplore team and Springer Nature have launched a new research project with the aim of developing new innovative solutions to support business processes in Springer Nature. This new initiative builds on our previous collaborations which focus on two research directions. The first one is Smart Topic Miner, a web application which uses semantic web […]

Smart Topic Miner shines at ISWC 2016

Last week Francesco Osborne attended the 15th edition of the International Semantic Web Conference (ISWC 2016) where he presented our work on the Smart Topic Miner (STM), the innovative application developed in collaboration with Springer Nature for automatically classifying research publications. STM was designed to classify proceedings and more in general any collection of articles […]

A new solution for classifying scholarly publications: Smart Topic Miner

The process of classifying scholarly outputs is crucial to ensure timely access to knowledge. This process is typically carried out manually by expert editors, leading to high costs and slow throughput. For these reasons, the Rexplore team, in collaboration with Springer Nature, created Smart Topic Miner (STM), a novel solution which uses semantic web technologies […]