Personalized keyword search on large RDF graphs based on pattern graph similarity

Souvik Brata Sinha, Xinge Lu, Dimitrios Theodoratos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

The structure of the ever increasing large RDF repositories is too complex to allow non-expert users extract useful information from them. Keyword search is an interesting alternative but in the context of RDF graph data, where query answers are RDF graph fragments, it faces two major problems: The query quality answer problem and the result computation algorithm scalability problem. In this paper we focus on empowering keyword search on RDF data by exploiting personalized information. We propose an original approach which exploits the structural summary of the RDF graph to generate pattern graphs for the input keyword query. Pattern graphs are structured conjunctive queries and are seen as possible interpretations of the unstructured keyword query. Personalized information is represented as collections of profile graphs, a concept similar to pattern graphs. The ranking of the results is achieved by measuring graph similarity between the user profile graph and the generated pattern graphs. Novel similarity metrics have been introduced which consider intrinsic and extrinsic similarity and take into account both structural and semantic characteristics of the pattern and profile graphs. Effectiveness and efficiency experimental results show that our approach can tackle the two major problems that hinder the widespread use of keyword search on RDF data.

Original languageEnglish (US)
Title of host publicationProceedings of the 22nd International Database Engineering and Applications Symposium, IDEAS 2018
EditorsBipin C. Desai
PublisherAssociation for Computing Machinery
Pages12-21
Number of pages10
ISBN (Electronic)9781450365277
DOIs
StatePublished - Jun 18 2018
Event22nd International Database Engineering and Applications Symposium, IDEAS 2018 - Villa San Giovanni, Italy
Duration: Jun 18 2018Jun 20 2018

Other

Other22nd International Database Engineering and Applications Symposium, IDEAS 2018
CountryItaly
CityVilla San Giovanni
Period6/18/186/20/18

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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