@article{3063950,
    title = "Full-text support for publish/subscribe ontology systems",
    author = "Zervakis, L. and Tryfonopoulos, C. and Skiadopoulos, S. and Koubarakis, M.",
    journal = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
    year = "2016",
    volume = "9678",
    pages = "233-249",
    publisher = "Springer-Verlag",
    doi = "10.1007/978-3-319-34129-3_15",
    keywords = "Indexing (of information), And filters;  Continuous queries;  Main memory;  Ontology system;  Orders of magnitude;  Publish/subscribe;  Query indexing;  State of the art, Semantic Web",
    abstract = "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. © Springer International Publishing Switzerland 2016."
}