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Building Knowledge Graph in Spark Without SPARQL

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Part of the Communications in Computer and Information Science book series (CCIS,volume 1285)

Abstract

Knowledge graphs, powerful assets for enhancing search and various data integration, are being essential in both academia and industry. In this paper we will demonstrate that knowledge graph abilities are much wider than search and data integration. We will do it in a twofold manner: 1) we will show how to build knowledge graph in Spark instead of using SPARQL language and how to explore data in DataFrames and GraphFrames; and 2) we will reveal Spark knowledge graph as a bridge between logical thinking and graph thinking for data mining.

Keywords

  • Knowledge graph
  • Spark
  • Scala
  • DataFrames
  • GraphFrames

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References

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  12. “Knowledge Graph for Data Mining” post. http://sparklingdataocean.com/2019/09/24/knowledgeGraphDataAnalysis/

  13. Drawing graphs with dot. https://www.ocf.berkeley.edu/~eek/index.html/tiny_examples/thinktank/src/gv1.7c/doc/dotguide.pdf

  14. Visual network analysis with Gephi. https://medium.com/@EthnographicMachines/visual-network-analysis-with-gephi-d6241127a336

  15. Motifs Findings in GraphFrames. https://www.waitingforcode.com/apache-spark-graphframes/motifs-finding-graphframes/read

  16. “Knowledge Graph for Data Integration” post. http://sparklingdataocean.com/2020/02/02/knowledgeGraphIntegration/

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Correspondence to Alex Romanova .

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Romanova, A. (2020). Building Knowledge Graph in Spark Without SPARQL. In: , et al. Database and Expert Systems Applications. DEXA 2020. Communications in Computer and Information Science, vol 1285. Springer, Cham. https://doi.org/10.1007/978-3-030-59028-4_9

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  • DOI: https://doi.org/10.1007/978-3-030-59028-4_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-59027-7

  • Online ISBN: 978-3-030-59028-4

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