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SciTo Trends: Visualising Scientific Topic Trends

  • Serafeim Chatzopoulos
  • Panagiotis Deligiannis
  • Thanasis VergoulisEmail author
  • Ilias Kanellos
  • Christos Tryfonopoulos
  • Theodore Dalamagas
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11799)

Abstract

Monitoring trends in scientific disciplines is a common task for researchers and other professionals in the broad research and academic community, like research and innovation policy makers and research fund managers. We demonstrate SciTo, a powerful tool that assists in the monitoring of trends in scientific disciplines. SciTo supports keyword-based search for the identification of scientific topics of interest and comparison of interesting topics to each other in terms of their popularity inside the academic community.

Keywords

Information retrieval Scientific impact Topic modeling 

Notes

Acknowledgments

We acknowledge support of this work by the project “Moving from Big Data Management to Data Science” (MIS 5002437/3) which is implemented under the Action “Re-inforcement of the Research and Innovation Infrastructure”, funded by the Operational Programme “Competitiveness, Entrepreneurship and Innovation” (NSRF 2014–2020) and co-financed by Greece and the European Union (European Regional Development Fund).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Serafeim Chatzopoulos
    • 1
    • 2
  • Panagiotis Deligiannis
    • 1
  • Thanasis Vergoulis
    • 2
    Email author
  • Ilias Kanellos
    • 2
    • 3
  • Christos Tryfonopoulos
    • 1
  • Theodore Dalamagas
    • 2
  1. 1.Department of Informatics and Tel/tionsUniversity of the PeloponneseTripoliGreece
  2. 2.IMSI - “Athena” Research & Innovation CenterAthensGreece
  3. 3.School of Electrical and Computer EngineeringNTUAAthensGreece

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