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Smart Topic Miner: Supporting Springer Nature Editors with Semantic Web Technologies

Osborne, Francesco; Salatino, Angelo; Birukou, Aliaksandr and Motta, Enrico (2016). Smart Topic Miner: Supporting Springer Nature Editors with Semantic Web Technologies. In: International Semantic Web Conference (ISWC 2016), 17-21 October 2016, Kobe, Japan.

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Abstract

Academic publishers, such as Springer Nature, annotate scholarly products with the appropriate research topics and keywords to facilitate the marketing process and to support (digital) libraries and academic search engines. This critical process is usually handled manually by experienced editors, leading to high costs and slow throughput. In this demo paper, we present Smart Topic Miner (STM), a semantic application designed to support the Springer Nature Computer Science editorial team in classifying scholarly publications. STM analyses conference proceedings and annotates them with a set of topics drawn from a large automatically generated ontology of research areas and a set of tags from Springer Nature Classification.

Item Type: Conference or Workshop Item
Keywords: Scholarly Data; Ontology Learning; Bibliographic Data; Scholarly Ontologies; Data Mining; Conference Proceedings; Metadata
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Interdisciplinary Research Centre: Centre for Research in Computing (CRC)
Item ID: 47086
Depositing User: Francesco Osborne
Date Deposited: 24 Aug 2016 14:44
Last Modified: 17 Nov 2016 15:32
URI: http://oro.open.ac.uk/id/eprint/47086
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