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Tag: Topic Classification

Smart Topics Miner 2: Improving Proceedings Retrievability at Springer Nature

By Angelo Salatino | 07 August 201917 October 2019• 9 minute read

Producing a robust and comprehensive representation of the research topics covered by a scientific publication is a crucial task that has a major impact on its retrievability and consequently on the diffusion of the relevant scientific ideas. Springer Nature, the world’s largest academic book publisher, has typically entrusted this task to the most expert editors, which had to manually analyse new books and produce a list of the most relevant topics. To support Springer Nature in this task, we developed Smart Topic Miner, an application that assists the editorial team in annotating proceedings books according to a large-scale ontology of research areas. Over the past three years, we evolved this application according to the editors’ feedback and developed a new engine, a new interface, and several other functionalities. In this demo paper, we present Smart Topic Miner 2, the most recent version of the tool, which is being regularly utilized by editors in Germany, China, Brazil, and Japan to annotate all book series covering conference proceedings in Computer Science, for a total of about 800 volumes per year.

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Improving Editorial Workflow and Metadata Quality at Springer Nature

By Angelo Salatino | 06 July 201929 October 2019• 3 minute read

Identifying the research topics that best describe the scope of a scientific publication is a crucial task for editors, in particular because the quality of these annotations determine how effectively users are able to discover the right content in online libraries. For this reason, Springer Nature, the world’s largest academic book publisher, has traditionally entrusted this task to their most expert editors. These editors manually analyse all new books, possibly including hundreds of chapters, and produce a list of the most relevant topics. Hence, this process has traditionally been very expensive, time-consuming, and confined to a few senior editors. For these reasons, back in 2016 we developed Smart Topic Miner (STM), an ontology-driven application that assists the Springer Nature editorial team in annotating the volumes of all books covering conference proceedings in Computer Science. Since then STM has been regularly used by editors in Germany, China, Brazil, India, and Japan, for a total of about 800 volumes per year. Over the past three years the initial prototype has iteratively evolved in response to feedback from the users and evolving requirements.

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Bibliographic Data big data clique community detection Conference Proceedings data mining data science Digital Libraries emerging topics ffmpeg graph igraph Knowledge Graph Machine Learning Matlab Metadata mksmart mobility Ontologies Ontology ontology engineering Ontology Learning phd podcasts Qt Framawork R research Research Dynamics Research Trend Detection rexplore Safety Scholarly Data Scholarly Ontologies science of science semantic web sparql Speech emotion recognition springer summer school Text Mining topic detection Topic Discovery Topic Emergence Detection topic ontology www

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Recent Posts

  • Clique Percolation Method in Python 29 December 2020
  • ISWC2020 – BEST DEMO OF THE DAY AWARD 24 December 2020
  • Applying Machine Learning Techniques to Big Data in the Scholarly Domain 12 November 2020
  • Finalists at DataIQ 2020 Awards 01 October 2020
  • The AIDA Dashboard: Analysing Conferences with Semantic Technologies 19 September 2020
  • AIDA Dashboard 01 September 2020
  • Databases and Information Systems in the AI Era: Contributions from ADBIS, TPDL and EDA 2020 Workshops and Doctoral Consortium 16 August 2020
  • ‘PhD Survival Guide’, Angelo and Akshika, The Open University 11 August 2020

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Bibliographic Data big data clique community detection Conference Proceedings data mining data science Digital Libraries emerging topics ffmpeg graph igraph Knowledge Graph Machine Learning Matlab Metadata mksmart mobility Ontologies Ontology ontology engineering Ontology Learning phd podcasts Qt Framawork R research Research Dynamics Research Trend Detection rexplore Safety Scholarly Data Scholarly Ontologies science of science semantic web sparql Speech emotion recognition springer summer school Text Mining topic detection Topic Discovery Topic Emergence Detection topic ontology www
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