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Building Knowledge Graph in Spark Without SPARQL

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Database and Expert Systems Applications (DEXA 2020)

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

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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.

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References

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  2. The Limitations of SPARQL. http://horicky.blogspot.com/2010/08/limitations-of-sparql.html

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  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: Kotsis, G., 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

  • eBook Packages: Computer ScienceComputer Science (R0)

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