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 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 […]
After the success of the past two editions, the third edition of the Semantics, Analytics, Visualisation: Enhancing Scholarly Data workshop (SAVE-SD) has been recently announced. SAVE-SD aims to bring together publishers, companies and researchers from different fields to bridge the gap between the theoretical and practical aspects in regards to scholarly data. The workshop was […]
Last week Francesco Osborne presented two research papers of our team at the 20th International Conference on Knowledge Engineering and Knowledge Management (EKAW 2016) in Bologna, Italy. The first one introduces TechMiner, a novel tool which combines NLP, machine learning and semantic technologies, for mining technologies from research publications and generating an OWL ontology describing […]
EKAW 2016 – TechMiner: Extracting Technologies from Academic Publications from Francesco Osborne
EKAW 2016 – Ontology Forecasting in Scientific Literature: Semantic Concepts Prediction Based on Innovation-Adoption Priors from Francesco Osborne
Automatic Classification of Springer Nature Proceedings with Smart Topic Miner from Francesco Osborne
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 […]
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 […]
On the 11th of April 2016, Angelo and Enrico won the Best Paper Award at the Workshop on Semantics, Analytics, Visualisation: Enhancing Scholarly Data (SAVE-SD 2016) of the 25th International World Wide Web Conference (WWW 2016) for the paper Detection of Embryonic Research Topics by Analysing Semantic Topic Networks. Just got the Best Paper Award at #savesd2016 .. […]
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