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Introducing Knowledge Graphs to Decision Support Systems Design

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Book cover Information Systems: Research, Development, Applications, Education (SIGSAND/PLAIS 2019)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 359))

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Abstract

Recent progress in cognitive technologies has driven decision support system (DSS) development in more complex directions. One of the main challenges in efficient DSS design is knowledge acquisition, especially in complicated and uncertain decision contexts. The more knowledge available to the system, the better decisions can be generated by a DSS. Representation of knowledge plays an important role in finding solutions to problems. With advances in the Semantic Web, knowledge can be represented in structured formats such as ontologies, which ease search and reasoning tasks. However, new data cannot be easily integrated nor updated in ontologies in real-time. Consequently, knowledge graphs (KGs) have emerged as a dynamic, scalable and domain independent form of knowledge representation. This paper explores how KGs can enhance the decision-making process in DSSs. Moreover, the paper presents a framework that may facilitate the integration of KGs into the DSS design.

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Notes

  1. 1.

    The figure was generated using NEO4j sandbox.

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Authors and Affiliations

  1. Virigina Commonwealth University, Richmond, VA, USA

    Samaa Elnagar & Heinz Roland Weistroffer

Authors
  1. Samaa Elnagar
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  2. Heinz Roland Weistroffer
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Corresponding authors

Correspondence to Samaa Elnagar or Heinz Roland Weistroffer .

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Editors and Affiliations

  1. Department of Business Informatics, University of Gdansk, Gdansk, Poland

    Stanisław Wrycza

  2. Department of Business Informatics, University of Gdansk, Gdansk, Poland

    Jacek Maślankowski

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Elnagar, S., Weistroffer, H.R. (2019). Introducing Knowledge Graphs to Decision Support Systems Design. In: Wrycza, S., Maślankowski, J. (eds) Information Systems: Research, Development, Applications, Education. SIGSAND/PLAIS 2019. Lecture Notes in Business Information Processing, vol 359. Springer, Cham. https://doi.org/10.1007/978-3-030-29608-7_1

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  • DOI: https://doi.org/10.1007/978-3-030-29608-7_1

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