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http://hdl.handle.net/2183/34574 Revisiting Compact RDF Stores Based on k2-Trees
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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.
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[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
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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 publication. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The final published paper is available online at: https: https://doi.org/10.1109/DCC47342.2020.00020
© 2020 IEEE. This version of the paper has been accepted for publication. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The final published paper is available online at: https: https://doi.org/10.1109/DCC47342.2020.00020







