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

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

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.

Original languageEnglish
Title of host publicationEntwicklungen, Chancen und Herausforderungen der Digitalisierung : Proceedings der 15. Internationalen Tagung Wirtschaftsinformatik 2020
EditorsN. Gronau, M. Heine, H. Krasnova, K. Pousttchi
Number of pages6
Volume1
Place of PublicationBerlin
PublisherGITO mbH Verlag
Publication date09.03.2020
Pages115-120
Article number8
ISBN (electronic)978-3-95545-335-0
DOIs
Publication statusPublished - 09.03.2020
EventInternationale Tagung Wirtschaftsinformatik - WI 2020: Changing Landscapes - Shaping Digital Transformation and its Impact - Universität Potsdam, Potsdam, Germany
Duration: 09.03.202011.03.2020
Conference number: 15
https://wi2020.de/de/start

Bibliographical note

Bd. 1: Zentrale Tracks. Motto “Changing Landscapes"

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

    Research areas

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

DOI

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