Social-Textual Query Processing on Graph Database Systems

  • Oshini Goonetilleke
  • Timos Sellis
  • Xiuzhen Zhang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10837)


Graph database systems are increasingly being used to store and query large-scale property graphs with complex relationships. Graph data, particularly the ones generated from social networks generally has text associated to the graph. Although graph systems provide support for efficient graph-based queries, there have not been comprehensive studies on how other dimensions, such as text, stored within a graph can work well together with graph traversals. In this paper we focus on a query that can process graph traversal and text search in combination in a graph database system and rank users measured as a combination of their social distance and the relevance of the text description to the query keyword. Our proposed algorithm leverages graph partitioning techniques to speed-up query processing along both dimensions. We conduct experiments on real-world large graph datasets and show benefits of our algorithm compared to several other baseline schemes.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Oshini Goonetilleke
    • 1
  • Timos Sellis
    • 2
  • Xiuzhen Zhang
    • 1
  1. 1.RMIT UniversityMelbourneAustralia
  2. 2.Swinburne University of TechnologyMelbourneAustralia

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