• Nov 28, 2023 News!Vol.9, No.2 has been published with online version.   [Click]
  • Jun 06, 2023 News!Vol.9, No.1 has been published with online version.   [Click]
  • May 27, 2022 News!Vol.8, No.1 has been published with online version.   [Click]
General Information
    • ISSN: 2382-6185
    • Abbreviated Title: Int. J. Knowl. Eng.
    • Frequency: Semiyearly
    • DOI: 10.18178/IJKE
    • Editor-in-Chief: Prof. Chen-Huei Chou
    • Executive Editor: Ms. Shira,W.Lu
    • Indexed by: Google Scholar, Crossref, ProQuest
    • E-mail: ijke@ejournal.net
Prof. Chen-Huei Chou
College of Charleston, SC, USA
It is my honor to be the editor-in-chief of IJKE. I will do my best to help develop this journal better.
IJKE 2021 Vol.7(1): 8-13 ISSN: 2382-6185
doi: 10.18178/ijke.2021.7.1.134

Automatic Information Extraction from Text-Based Requirements

Simon Fritz, Vethiga Srikanthan, Ryan Arbai, Chenwei Sun, Jivka Ovtcharova, and Hendro Wicaksono

Abstract—Requirements form the legal basis for many development pro-jects. They are usually exchanged between customer and supplier in the form of product and requirements specifications and re-quire a subsequent integration effort into the corresponding requirements management solutions. Especially for small and medium-sized enterprises (SME), which mainly use office solutions for the management of requirements, this involves a very high integration effort, which is why this is usually only partially managed or not managed at all. Software solutions available on the market already offer support, but they are too expensive or complex, especially for small companies. The project DAM4KMU, funded by German Federal Ministry for Education and Research (BMBF), addresses this challenge and by enabling SMEs from Germany to integrate requirement documents automatically into existing requirement structures with the help of NLP-based techniques. For this purpose, the documents to be processed are divided into semantic roles, which can then be transferred into a semantic data structure. This in turn enables an automatic linking of the requirements and system components, which reduces the manual effort and avoids possible errors.

Index Terms—Requirements engineering, NLP, context-sensitive assistance.

Simon Fritz, Ryan Arbai, and Chenwei Sun are with the Intelligent Systems and Production Engineering (ISPE), Research Center for Information Technology (FZI), Karlsruhe, Germany (e-mail: fritz@fzi.de, rarbai@fzi.de, sun@fzi.de). Vethiga Srikanthan is with the Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany (e-mail: vethisri@gmail.com). Jivka Ovtcharova is with the Institute for Information Management in Engineering (IMI), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany (e-mail: jivka.ovtcharova@kit.edu). Hendro Wicaksono is with the Industrial Engineering Mathematics & Logistics, Jacobs University Bremen gGmbH, Bremen, Germany (e-mail: h.wicaksono@jacobs-university.de).


Cite: Simon Fritz, Vethiga Srikanthan, Ryan Arbai, Chenwei Sun, Jivka Ovtcharova, and Hendro Wicaksono, "Automatic Information Extraction from Text-Based Requirements," International Journal of Knowledge Engineering vol. 7, no. 1, pp. 8-13, 2021.

Copyright © 2021 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
Copyright © 2008-2023   International Journal of Knowledge Engineering. All rights reserved.
E-mail: ijke@ejournal.net