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Multi-modal Terminology Management

Corpora, Data Models, and Implementations in TermStar

  • Conference paper
  • First Online:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1752))

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Abstract

Terminology is a key part of the translation process. Nonetheless, the benefits of implementing a terminology management workflow using specialist tools and processes is sometimes disregarded, as the benefits in terms of ROI are not always easy to evaluate. As a result, the use of spreadsheets and other inappropriate tools leads to fragmented and inefficient terminology management processes.

In this paper we set out to describe an efficient terminology management workflow which has been developed for real terminology projects. We will also assess the benefits of implementing a proper terminology management workflow where all stakeholders (terminologists, linguists, authors, and end users) are involved. We will highlight the benefits of using a Terminology Management System (TMS) such as TermStar, which can make use of parallel corpora and collaboration functions to streamline the entire process, from terminological extraction to glossary approval and maintenance.

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Author information

Authors and Affiliations

  1. STAR7, S.p.A., Alessandria, Italy

    Enrico Giai, Nicola Poeta & David Turnbull

Authors
  1. Enrico Giai
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  2. Nicola Poeta
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  3. David Turnbull
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Corresponding author

Correspondence to Enrico Giai .

Editor information

Editors and Affiliations

  1. University of Sydney, Sydney, Australia

    Irena Koprinska

  2. University of Bari Aldo Moro, Bari, Italy

    Paolo Mignone

  3. University of Pisa, Pisa, Italy

    Riccardo Guidotti

  4. Warsaw University of Technology, Warsaw, Poland

    Szymon Jaroszewicz

  5. Heidelberg University, Heidelberg, Germany

    Holger Fröning

  6. UniCredit, Rome, Italy

    Francesco Gullo

  7. University of Lisbon, Lisbon, Portugal

    Pedro M. Ferreira

  8. Roche, Basel, Switzerland

    Damian Roqueiro

  9. Barcelona Supercomputing Center, Barcelona, Spain

    Gaia Ceddia

  10. Halmstad University, Halmstad, Sweden

    Slawomir Nowaczyk

  11. University of Porto, Porto, Portugal

    João Gama

  12. University of Porto, Porto, Portugal

    Rita Ribeiro

  13. UPC BarcelonaTech, Barcelona, Spain

    Ricard Gavaldà

  14. University of Naples Federico II, Naples, Italy

    Elio Masciari

  15. University of North Carolina, Charlotte, USA

    Zbigniew Ras

  16. ICAR-CNR, Rende, Italy

    Ettore Ritacco

  17. University of Pisa, Pisa, Italy

    Francesca Naretto

  18. Aalen University of Applied Sciences, Aalen, Germany

    Andreas Theissler

  19. Warsaw University of Technology, Warszaw, Poland

    Przemyslaw Biecek

  20. KU Leuven, Leuven, Belgium

    Wouter Verbeke

  21. University of Duisburg-Essen, Essen, Germany

    Gregor Schiele

  22. Graz University of Technology, Graz, Austria

    Franz Pernkopf

  23. AMD, Dublin, Ireland

    Michaela Blott

  24. UniCredit, Rome, Italy

    Ilaria Bordino

  25. UniCredit, Milan, Italy

    Ivan Luciano Danesi

  26. National Agency for New Technologies, Rome, Italy

    Giovanni Ponti

  27. Unicredit, Rome, Italy

    Lorenzo Severini

  28. University of Bari Aldo Moro, Bari, Italy

    Annalisa Appice

  29. University of Bari Aldo Moro, Bari, Italy

    Giuseppina Andresini

  30. University of Lisbon, Lisbon, Portugal

    Ibéria Medeiros

  31. University of Lisbon, Lisbon, Portugal

    Guilherme Graça

  32. Northwestern University, Chicago, USA

    Lee Cooper

  33. Roche, Basel, Switzerland

    Naghmeh Ghazaleh

  34. University of Lausanne, Lausanne, Switzerland

    Jonas Richiardi

  35. Novartis, Basel, Switzerland

    Diego Saldana

  36. Novartis, Basel, Switzerland

    Konstantinos Sechidis

  37. Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy

    Arif Canakoglu

  38. Politecnico di Milano, Milan, Italy

    Sara Pido

  39. Politecnico di Milano, Milan, Italy

    Pietro Pinoli

  40. University of Waikato, Hamilton, New Zealand

    Albert Bifet

  41. Halmstad University, Halmstad, Sweden

    Sepideh Pashami

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Giai, E., Poeta, N., Turnbull, D. (2023). Multi-modal Terminology Management. In: Koprinska, I., et al. Machine Learning and Principles and Practice of Knowledge Discovery in Databases. ECML PKDD 2022. Communications in Computer and Information Science, vol 1752. Springer, Cham. https://doi.org/10.1007/978-3-031-23618-1_14

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  • DOI: https://doi.org/10.1007/978-3-031-23618-1_14

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-23617-4

  • Online ISBN: 978-3-031-23618-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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