Using CNNs to Detect Graphical Representations of Structural Equation Models in IS Papers

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

Authors

Literature reviews are an essential but time-consuming part of every research endeavor and play an important role in the quality of the research findings. Traditional tools and literature databases only make use of the textual information and do not consider graphical representations like figures of structural equation models (SEMs). These models are often used in empirical studies to visualize theoretical models and key results. We design and implement an application for image recognition to simplify the search for relevant papers, by automatically recognizing SEM figures in scientific papers stored as PDF files. To classify whether a page in a paper contains an SEM figure we make use of convolutional neural networks and achieve an F1 score of 98,7% together with a recall of 100% for the SEM class. We further describe how we intend to automatically extract information from these SEM figures.

OriginalspracheEnglisch
TitelEntwicklungen, Chancen und Herausforderungen der Digitalisierung : Proceedings der 15. Internationalen Tagung Wirtschaftsinformatik 2020
HerausgeberN. Gronau, M. Heine, H. Krasnova, K. Pousttchi
Anzahl der Seiten6
Band1
ErscheinungsortBerlin
VerlagGITO mbH Verlag
Erscheinungsdatum09.03.2020
Seiten115-120
Aufsatznummer8
ISBN (elektronisch)978-3-95545-335-0
DOIs
PublikationsstatusErschienen - 09.03.2020
VeranstaltungInternationale Tagung Wirtschaftsinformatik - WI 2020: Changing Landscapes - Shaping Digital Transformation and its Impact - Universität Potsdam, Potsdam, Deutschland
Dauer: 09.03.202011.03.2020
Konferenznummer: 15
https://wi2020.de/de/start

Bibliographische Notiz

Publisher Copyright:
© Proceedings of the 15th International Conference on Business Information Systems 2020 "Developments, Opportunities and Challenges of Digitization", WIRTSCHAFTSINFORMATIK 2020.

    Fachgebiete

  • Wirtschaftsinformatik - Structural equation models, deep neural networks, information extraction, literature review

DOI

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  1. Barbara Romero

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