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A Graph DB-Based Solution for Semantic Technologies in the Future Internet

Author

Listed:
  • Stefano Ferilli

    (Department of Computer Science, University of Bari, 70125 Bari, Italy)

  • Eleonora Bernasconi

    (Department of Computer Science, University of Bari, 70125 Bari, Italy)

  • Davide Di Pierro

    (Department of Computer Science, University of Bari, 70125 Bari, Italy)

  • Domenico Redavid

    (Department of Computer Science, University of Bari, 70125 Bari, Italy)

Abstract

With the progressive improvements in the power, effectiveness, and reliability of AI solutions, more and more critical human problems are being handled by automated AI-based tools and systems. For more complex or particularly critical applications, the level of knowledge, not just information, must be handled by systems where explicit relationships among objects are represented and processed. For this purpose, the knowledge representation branch of AI proposes Knowledge Graphs, widely used in the Semantic Web, where different online applications may interact by understanding the meaning of the data they process and exchange. This paper describes a framework and online platform for the Internet-based knowledge graph definition, population, and exploitation based on the LPG graph model. Its main advantages are its efficiency and representational power and the wide range of functions that it provides to its users beyond traditional Semantic Web reasoning: network analysis, data mining, multistrategy reasoning, and knowledge browsing. Still, it can also be mapped onto the SW.

Suggested Citation

  • Stefano Ferilli & Eleonora Bernasconi & Davide Di Pierro & Domenico Redavid, 2023. "A Graph DB-Based Solution for Semantic Technologies in the Future Internet," Future Internet, MDPI, vol. 15(10), pages 1-28, October.
    • Handle: RePEc:gam:jftint:v:15:y:2023:i:10:p:345-:d:1264141
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    References listed on IDEAS

    as
    1. Vaidya, Omkarprasad S. & Kumar, Sushil, 2006. "Analytic hierarchy process: An overview of applications," European Journal of Operational Research, Elsevier, vol. 169(1), pages 1-29, February.
    2. Lyubomir Penev & Mariya Dimitrova & Viktor Senderov & Georgi Zhelezov & Teodor Georgiev & Pavel Stoev & Kiril Simov, 2019. "OpenBiodiv: A Knowledge Graph for Literature-Extracted Linked Open Data in Biodiversity Science," Publications, MDPI, vol. 7(2), pages 1-16, May.
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