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arXiv · 1911.08372

Improved Compressed String Dictionaries

Nieves R. Brisaboa·Ana Cerdeira-Pena·Guillermo de Bernardo·Gonzalo Navarro
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Abstract

We introduce a new family of compressed data structures to efficiently store and query large string dictionaries in main memory. Our main technique is a combination of hierarchical Front-coding with ideas from longest-common-prefix computation in suffix arrays. Our data structures yield relevant space-time tradeoffs in real-world dictionaries. We focus on two domains where string dictionaries are extensively used and efficient compression is required: URL collections, a key element in Web graphs and applications such as Web mining; and collections of URIs and literals, the basic components of RDF datasets. Our experiments show that our data structures achieve better compression than the state-of-the-art alternatives while providing very competitive query times.

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Nieves R. Brisaboa, Ana Cerdeira-Pena, Guillermo de Bernardo, Gonzalo Navarro. 2019-11-19. Improved Compressed String Dictionaries. https://doi.org/10.1145/3357384.3357972

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