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STAMP 4 NLP – An Agile Framework for Rapid Quality-Driven NLP Applications Development

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Quality of Information and Communications Technology (QUATIC 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1439))

Abstract

The progress in natural language processing (NLP) research over the last years, offers novel business opportunities for companies, as automated user interaction or improved data analysis. Building sophisticated NLP applications requires dealing with modern machine learning (ML) technologies, which impedes enterprises from establishing successful NLP projects. Our experience in applied NLP research projects shows that the continuous integration of research prototypes in production-like environments with quality assurance builds trust in the software and shows convenience and usefulness regarding the business goal. We introduce STAMP 4 NLP as an iterative and incremental process model for developing NLP applications. With STAMP 4 NLP, we merge software engineering principles with best practices from data science. Instantiating our process model allows efficiently creating prototypes by utilizing templates, conventions, and implementations, enabling developers and data scientists to focus on the business goals. Due to our iterative-incremental approach, businesses can deploy an enhanced version of the prototype to their software environment after every iteration, maximizing potential business value and trust early and avoiding the cost of successful yet never deployed experiments.

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Notes

  1. 1.

    https://github.com/philipp-kohl/stamp4nlp.

  2. 2.

    Similar to https://drivendata.github.io/cookiecutter-data-science/.

  3. 3.

    https://spacy.io/.

  4. 4.

    https://pytorch.org/.

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Author information

Authors and Affiliations

  1. FH Aachen - University of Applied Sciences, 52428, Jülich, Germany

    Philipp Kohl, Oliver Schmidts, Lars Klöser, Henri Werth & Bodo Kraft

  2. University of Kassel, 34127, Kassel, Germany

    Albert Zündorf

Authors
  1. Philipp Kohl
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  2. Oliver Schmidts
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  3. Lars Klöser
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  4. Henri Werth
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  5. Bodo Kraft
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  6. Albert Zündorf
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Corresponding author

Correspondence to Philipp Kohl .

Editor information

Editors and Affiliations

  1. Faculty of Engineering of the University of Porto, Porto, Portugal

    Ana C. R. Paiva

  2. Institut Polytechnique de Paris, Paris, France

    Ana Rosa Cavalli

  3. University of Algarve, Faro, Portugal

    Paula Ventura Martins

  4. University of Castila-La Mancha, Ciudad Real, Ciudad Real, Spain

    Ricardo Pérez-Castillo

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Kohl, P., Schmidts, O., Klöser, L., Werth, H., Kraft, B., Zündorf, A. (2021). STAMP 4 NLP – An Agile Framework for Rapid Quality-Driven NLP Applications Development. In: Paiva, A.C.R., Cavalli, A.R., Ventura Martins, P., Pérez-Castillo, R. (eds) Quality of Information and Communications Technology. QUATIC 2021. Communications in Computer and Information Science, vol 1439. Springer, Cham. https://doi.org/10.1007/978-3-030-85347-1_12

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  • DOI: https://doi.org/10.1007/978-3-030-85347-1_12

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  • Online ISBN: 978-3-030-85347-1

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