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Mining Social Networks from Linked Open Data

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Graph-Based Representation and Reasoning (ICCS 2019)

Abstract

The richness and openness of Linked Open Data (LOD) make them invaluable resources of information, and create new opportunities for many areas of application. In this paper, we address the exploitation of LOD by utilizing SPARQL queries in order to extract social networks of entities. This enables the application of techniques from Social Network Analysis to study social interactions among entities, providing deep insights into their latent social structure.

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Notes

  1. 1.

    http://yago-knowledge.org.

  2. 2.

    https://wiki.dbpedia.org.

  3. 3.

    http://bibliographic-ontology.org/.

  4. 4.

    https://dailymed.nlm.nih.gov/dailymed/.

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Correspondence to Raji Ghawi .

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Ghawi, R., Pfeffer, J. (2019). Mining Social Networks from Linked Open Data. In: Endres, D., Alam, M., Şotropa, D. (eds) Graph-Based Representation and Reasoning. ICCS 2019. Lecture Notes in Computer Science(), vol 11530. Springer, Cham. https://doi.org/10.1007/978-3-030-23182-8_16

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  • DOI: https://doi.org/10.1007/978-3-030-23182-8_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-23181-1

  • Online ISBN: 978-3-030-23182-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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