Social-Textual Query Processing on Graph Database Systems

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10837)

Abstract

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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