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International Conference on Research Challenges in Information Science

RCIS 2022: Research Challenges in Information Science pp 761–768Cite as

ANGLEr: A Next-Generation Natural Language Exploratory Framework

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Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 446))

Abstract

Natural language processing is used for solving a wide variety of problems. Some scholars and interest groups working with language resources are not well versed in programming, so there is a need for a good graphical framework that allows users to quickly design and test natural language processing pipelines without the need for programming. The existing frameworks do not satisfy all the requirements for such a tool. We, therefore, propose a new framework that provides a simple way for its users to build language processing pipelines. It also allows a simple programming language agnostic way for adding new modules, which will help the adoption by natural language processing developers and researchers. The main parts of the proposed framework consist of (a) a pluggable Docker-based architecture, (b) a general data model, and (c) APIs description along with the graphical user interface. The proposed design is being used for implementation of a new natural language processing framework, called ANGLEr.

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Notes

  1. 1.

    The number of downloads was recorded by https://sourceforge.net.

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Authors and Affiliations

  1. University of Ljubljana, Ljubljana, Slovenia

    Timotej Knez, Marko Bajec & Slavko Žitnik

Authors
  1. Timotej Knez
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  2. Marko Bajec
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  3. Slavko Žitnik
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Corresponding author

Correspondence to Timotej Knez .

Editor information

Editors and Affiliations

  1. University of Twente, Enschede, The Netherlands

    Renata Guizzardi

  2. University of Geneva, CUI, Carouge, Switzerland

    Jolita Ralyté

  3. Polytechnic University of Catalonia, Barcelona, Spain

    Xavier Franch

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© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Knez, T., Bajec, M., Žitnik, S. (2022). ANGLEr: A Next-Generation Natural Language Exploratory Framework. In: Guizzardi, R., Ralyté, J., Franch, X. (eds) Research Challenges in Information Science. RCIS 2022. Lecture Notes in Business Information Processing, vol 446. Springer, Cham. https://doi.org/10.1007/978-3-031-05760-1_53

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  • DOI: https://doi.org/10.1007/978-3-031-05760-1_53

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-05759-5

  • Online ISBN: 978-3-031-05760-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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