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

By Angelo Salatino | 16 October 201616 May 2019• 2 minute read

 

STM interface

“Smart Topic Miner: Supporting Springer Nature Editors with Semantic Web Technologies” is poster paper presented at the Poster and Demo session [D45] on Wednesday 19th October 2016 at the 15th International Semantic Web Conference in Kobe, Japan

Authors:

Francesco Osborne, Angelo Antonio Salatino, Aliaksandr Birukou and Enrico Motta

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.

Download paper (via ORO): link

Download paper (via CEUR): link

Proceedings: link

Link to the DEMO: http://rexplore.kmi.open.ac.uk/STM_demo/ 

Poster:

Smart Topic Miner, presented poster.
Smart Topic Miner, presented poster.
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Bibliographic Data Conference Proceedings data mining Metadata Ontology Learning Scholarly Data Scholarly Ontologies

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Bibliographic Data big data clique Conference Proceedings cso data mining data science Digital Libraries emerging topics ffmpeg graph Knowledge Graph Knowledge Graphs Machine Learning Matlab Metadata mksmart mobility Ontologies Ontology Ontology Learning phd podcasts Qt Framawork R Research Dynamics research topics Research Trend Detection Research Trends Safety Scholarly Communication Scholarly Data Scholarly Ontologies science of science semantic web Semantic Web Technologies sparql Speech emotion recognition springer Text Mining topic detection Topic Discovery Topic Emergence Detection topic ontology Word Embeddings

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  • Integrating Conversational Agents and Knowledge Graphs Within the Scholarly Domain 18 March 2023
  • R-Classify: Extracting Research Papers’ Relevant Concepts from a Controlled Vocabulary 12 November 2022
  • Leveraging Knowledge Graph Technologies to Assess Journals and Conferences at Springer Nature 12 November 2022
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Bibliographic Data big data clique Conference Proceedings cso data mining data science Digital Libraries emerging topics ffmpeg graph Knowledge Graph Knowledge Graphs Machine Learning Matlab Metadata mksmart mobility Ontologies Ontology Ontology Learning phd podcasts Qt Framawork R Research Dynamics research topics Research Trend Detection Research Trends Safety Scholarly Communication Scholarly Data Scholarly Ontologies science of science semantic web Semantic Web Technologies sparql Speech emotion recognition springer Text Mining topic detection Topic Discovery Topic Emergence Detection topic ontology Word Embeddings
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