KEOPS: Knowledge ExtractOr Pipeline System | SpringerLink
Skip to main content
Springer Nature Link
Log in

KEOPS: Knowledge ExtractOr Pipeline System

  • Conference paper
  • First Online:
Research Challenges in Information Science (RCIS 2021)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 415))

Included in the following conference series:

  • 1489 Accesses

Abstract

The KEOPS platform applies text mining approaches (e.g. classification, terminology and named entity extraction) to generate knowledge about each text and group of texts extracted from documents, web pages, or databases. KEOPS is currently implemented on real data of a project dedicated to Food security, for which preliminary results are presented.

Supported by Leap4FNSSA H2020 project, SFS-33-2018, grant agreement 817663.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
JPY 3498
Price includes VAT (Japan)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
JPY 13727
Price includes VAT (Japan)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
JPY 17159
Price includes VAT (Japan)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    https://www.leap4fnssa.eu/.

  2. 2.

    http://www.fao.org/agrovoc/.

  3. 3.

    http://tubo.lirmm.fr/biotex.

  4. 4.

    https://spacy.io/.

  5. 5.

    https://library.wur.nl/WebQuery/leap4fnssa-projects/.

  6. 6.

    The multi-layer perceptron uses the default configuration available in the scikit-learn library.

References

  1. Aubin, S., Hamon, T.: Improving term extraction with terminological resources. In: Salakoski, T., Ginter, F., Pyysalo, S., Pahikkala, T. (eds.) FinTAL 2006. LNCS (LNAI), vol. 4139, pp. 380–387. Springer, Heidelberg (2006). https://doi.org/10.1007/11816508_39

    Chapter  Google Scholar 

  2. Barbier, M., Cointet, J.P.: Reconstruction of socio-semantic dynamics in sciences-society networks: Methodology and epistemology of large textual corpora analysis. Science and Democracy Network, Annual Meeting (2012)

    Google Scholar 

  3. Frantzi, K., Ananiadou, S., Mima, H.: Automatic recognition of multi-word terms: the c-value/nc-value method. Int. J. Digital Libraries 3(2), 115–130 (2000)

    Article  Google Scholar 

  4. Lossio-Ventura, J., Jonquet, C., Roche, M., Teisseire, M.: Biomedical term extraction: overview and a new methodology. Inf. Retr. J. 19(1–2), 59–99 (2016)

    Article  Google Scholar 

  5. Nedellec, C., Golik, W., Aubin, S., Bossy, R.: Building large lexicalized ontologies from text: a use case in automatic indexing of biotechnology patents. In: Proceedings of EKAW, pp. 514–523 (2010)

    Google Scholar 

  6. Paumier, S.: Unitex - Manuel d’utilisation, November 2011. https://hal.archives-ouvertes.fr/hal-00639621, working paper or preprint

  7. Roche, M., et al.: LEAP4FNSSA (WP3 - KMS): Terminology for KEOPS - Dataverse (2020). http://doi.org/10.18167/DVN1/GQ8DPL

  8. Silberztein, M.: La formalisation des langues : l’approche de NooJ. ISTE, London (2015)

    Google Scholar 

Download references

Acknowledgement

We thank the WP3 members of the LEAP4FNSSA project for their contribution to the indexing and classification tasks. We thank Xavier Rouviere for his contribution to the development of the user interface.

Author information

Authors and Affiliations

  1. CIRAD, UPR AIDA, 34398, Montpellier, France

    Pierre Martin

  2. AIDA, Univ Montpellier, CIRAD, Montpellier, France

    Pierre Martin

  3. CIRAD,DSI, 34398, Montpellier, France

    Thierry Helmer & Julien Rabatel

  4. CIRAD,UMR TETIS, 34398, Montpellier, France

    Mathieu Roche

  5. TETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, INRAE, Montpellier, France

    Mathieu Roche

Authors
  1. Pierre Martin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Thierry Helmer
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Julien Rabatel
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Mathieu Roche
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Pierre Martin .

Editor information

Editors and Affiliations

  1. Conservatoire National des Arts et Métiers, Paris, France

    Samira Cherfi

  2. Fondazione Bruno Kessler, Trento, Italy

    Anna Perini

  3. University Paris 1 Panthéon-Sorbonne, Paris, France

    Selmin Nurcan

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Martin, P., Helmer, T., Rabatel, J., Roche, M. (2021). KEOPS: Knowledge ExtractOr Pipeline System. In: Cherfi, S., Perini, A., Nurcan, S. (eds) Research Challenges in Information Science. RCIS 2021. Lecture Notes in Business Information Processing, vol 415. Springer, Cham. https://doi.org/10.1007/978-3-030-75018-3_36

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-75018-3_36

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-75017-6

  • Online ISBN: 978-3-030-75018-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics