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DBkWik++- Multi Source Matching of Knowledge Graphs

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Knowledge Graphs and Semantic Web (KGSWC 2022)

Abstract

Large knowledge graphs like DBpedia and YAGO are always based on the same source, i.e., Wikipedia. But there are more wikis that contain information about long-tail entities such as wiki hosting platforms like Fandom. In this paper, we present the approach and analysis of DBkWik++, a fused Knowledge Graph from thousands of wikis. A modified version of the DBpedia framework is applied to each wiki which results in many isolated Knowledge Graphs. With an incremental merge based approach, we reuse one-to-one matching systems to solve the multi source KG matching task. Based on this alignment we create a consolidated knowledge graph with more than 15 million instances.

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Notes

  1. 1.

    https://lod-cloud.net.

  2. 2.

    https://www.fandom.com.

  3. 3.

    https://en.wikipedia.org/wiki/Wikipedia:Notability_(people).

  4. 4.

    https://memory-alpha.fandom.com/wiki/Betty_Riker.

  5. 5.

    https://community.fandom.com/wiki/Help:Database_download.

  6. 6.

    https://github.com/WikiTeam/wikiteam.

  7. 7.

    a template in MediaWiki which usually contains the text infobox to visualize important information at the top right corner of a page.

  8. 8.

    http://mappings.dbpedia.org.

  9. 9.

    https://community.fandom.com/wiki/WAM_Hall_of_Fame.

  10. 10.

    https://lyrics.fandom.com.

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Correspondence to Sven Hertling .

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Hertling, S., Paulheim, H. (2022). DBkWik++- Multi Source Matching of Knowledge Graphs. In: Villazón-Terrazas, B., Ortiz-Rodriguez, F., Tiwari, S., Sicilia, MA., Martín-Moncunill, D. (eds) Knowledge Graphs and Semantic Web . KGSWC 2022. Communications in Computer and Information Science, vol 1686. Springer, Cham. https://doi.org/10.1007/978-3-031-21422-6_1

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  • DOI: https://doi.org/10.1007/978-3-031-21422-6_1

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