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A Framework for Knowledge Representation Integrated with Dynamic Network Analysis

  • Conference paper
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Emerging Trends and Applications in Artificial Intelligence ( ICETAI 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 960))

  • 28 Accesses

Abstract

Understanding the information residing in any system is of crucial importance. Knowledge Graphs are a tool for achieving such kinds of goals, as they hold the semantic interaction across the entities and, using links, connect them in a better representable way. In this paper, we proposed a dynamic network analysis framework for understanding the evolution of Knowledge Graphs across timelines. To validate our findings, we applied a thorough analysis of the movie recommendation Knowledge Graph, where we considered different snapshots of it. For example, past (historical information), present (current snapshot), and future (predictions based on historical data) information. For the predictions, we employ Graph Neural Network (GNN) modeling. We also compared our recommendation model with the latest related studies and achieved considerable results.

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Notes

  1. 1.

    https://www.imdb.com/interfaces/.

  2. 2.

    https://cytoscape.org/.

  3. 3.

    https://neo4j.com/.

  4. 4.

    https://www.mathworks.com/products/matlab.html.

  5. 5.

    https://github.com/neo4j-graph-examples/recommendations/tree/main/data Dataset is downloadable from the mentioned link..

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Acknowledgement

This research is funded by the PON Program and the University of Urbino Carlo Bo under matriculation number: 317840.

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Authors and Affiliations

  1. Universit’a degli Studi di Urbino Carlo Bo, Urbino, 61029, Italy

    Siraj Munir & Stefano Ferretti

  2. National University of Emerging Sciences, Karachi, 74200, Pakistan

    Rauf Ahmed Shams Malick

Authors
  1. Siraj Munir
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  2. Stefano Ferretti
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  3. Rauf Ahmed Shams Malick
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Corresponding author

Correspondence to Siraj Munir .

Editor information

Editors and Affiliations

  1. Ingenium Research Group, University of Castilla-La Mancha, Ciudad Real, Spain

    Fausto Pedro García Márquez

  2. National University of Computer and Emerging Sciences, Islamabad, Pakistan

    Akhtar Jamil

  3. Department of Computer Engineering, Istinye University, Istanbul, Türkiye

    Alaa Ali Hameed

  4. Ingenium Research Group, University of Castilla-La Mancha (UCLM), Ciudad Real, Spain

    Isaac Segovia Ramírez

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Munir, S., Ferretti, S., Malick, R.A.S. (2024). A Framework for Knowledge Representation Integrated with Dynamic Network Analysis. In: García Márquez, F.P., Jamil, A., Hameed, A.A., Segovia Ramírez, I. (eds) Emerging Trends and Applications in Artificial Intelligence. ICETAI 2023. Lecture Notes in Networks and Systems, vol 960. Springer, Cham. https://doi.org/10.1007/978-3-031-56728-5_4

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  • DOI: https://doi.org/10.1007/978-3-031-56728-5_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-56727-8

  • Online ISBN: 978-3-031-56728-5

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