Hybrid index structure based on MBB approximation for linked data

Yongju Lee, Yu Xiang Sun

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Although a pragmatic approach towards achieving Semantic Web has gained some traction with Linked Data, there are still a lot of open problems in the area of Linked Data. Because Linked Data are modeled as RDF graphs, we cannot directly adopt existing solutions from database systems or Web technologies. This paper presents a hybrid method between the centralized approach and the distributed approach based on query processing to increase the join query performance. Using auxiliary indexes we can retrieve distributed data resources participating on a query result, rapidly reducing the amount of data that are really needed to be accessed on-demand. The performance of the proposed index structure is compared with some existing methods on a real RDF dataset. Our method outperforms the existing methods due to its ability to reduce a large amount of irrelevant resources.

Original languageEnglish
Title of host publicationProceedings of the 10th International Conference on Computer Modeling and Simulation, ICCMS 2018
PublisherAssociation for Computing Machinery
Pages101-104
Number of pages4
ISBN (Electronic)9781450363396
DOIs
StatePublished - 8 Jan 2018
Event10th International Conference on Computer Modeling and Simulation, ICCMS 2018 - Sydney, Australia
Duration: 8 Jan 201810 Jan 2018

Publication series

NameACM International Conference Proceeding Series

Conference

Conference10th International Conference on Computer Modeling and Simulation, ICCMS 2018
Country/TerritoryAustralia
CitySydney
Period8/01/1810/01/18

Keywords

  • Hybrid index structure
  • Join query
  • Linked Data
  • Minimum bounding box
  • RDF
  • SPARQL

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