Miguel A. Martínez-Prieto

  1. Compressed k2-Triples for Full-In-Memory RDF Engines.

    Authors: Sandra Álvarez-García, Nieves R. Brisaboa, Javier D. Fernández, Miguel A. Martínez-Prieto
    Subjects: Information Retrieval
    Abstract

    Current "data deluge" has flooded the Web of Data with very large RDF
    datasets. They are hosted and queried through SPARQL endpoints which act as
    nodes of a semantic net built on the principles of the Linked Data project.
    Although this is a realistic philosophy for global data publishing, its query
    performance is diminished when the RDF engines (behind the endpoints) manage
    these huge datasets. Their indexes cannot be fully loaded in main memory, hence
    these systems need to perform slow disk accesses to solve SPARQL queries.

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