Revisiting Compact RDF Stores Based on k2-Trees

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Revisiting Compact RDF Stores Based on k2-TreesFecha
2020-03Cita bibliográfica
N. R. Brisaboa, A. Cerdeira-Pena, G. De Bernardo, y A. Fariña, «Revisiting Compact RDF Stores Based on k2-Trees», en 2020 Data Compression Conference (DCC), mar. 2020, pp. 123-132. doi: 10.1109/DCC47342.2020.00020.
Resumen
[Abstract]: We present a new compact representation to efficiently store and query large RDF datasets in main memory. Our proposal, called BMatrix, is based on the k 2 -tree, a data structure devised to represent binary matrices in a compressed way, and aims at improving the results of previous state-of-the-art alternatives, especially in datasets with a relatively large number of predicates. We introduce our technique, together with some improvements on the basic k 2 -tree that can be applied to our solution in order to boost compression. Experimental results in the flagship RDF dataset DBPedia show that our proposal achieves better compression than existing alternatives, while yielding competitive query times, particularly in the most frequent triple patterns and in queries with unbound predicate, in which we outperform existing solutions
Palabras clave
RDF
Compact data structures
K2 trees
Compact data structures
K2 trees
Descripción
Presented at the 2020 Data Compression Conference (DCC), Snowbird, UT, USA, 24-27 March 2020 © 2020 IEEE. This version of the paper has been accepted for
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https://doi.org/10.1109/DCC47342.2020.00020
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ISSN
2375-0359