Full-Text Support for Publish/Subscribe Ontology Systems

  • Lefteris ZervakisEmail author
  • Christos TryfonopoulosEmail author
  • Spiros Skiadopoulos
  • Manolis Koubarakis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9678)


In this work, we envision a publish/subscribe ontology system that is able to index large numbers of expressive continuous queries and filter them against RDF data that arrive in a streaming fashion. To this end, we propose a SPARQL extension that supports the creation of full-text continuous queries and propose a family of main-memory query indexing algorithms which perform matching at low complexity and minimal filtering time. We experimentally compare our approach against a state-of-the-art competitor (extended to handle indexing of full-text queries) both on structural and full-text tasks using real-world data. Our approach proves two orders of magnitude faster than the competitor in all types of filtering tasks.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Department of Informatics and TelecommunicationsUniversity of PeloponneseTripolisGreece
  2. 2.Department of Informatics and TelecommunicationsUniveristy of AthensAthensGreece

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