Improved compressed string dictionaries

8Citations
Citations of this article
21Readers
Mendeley users who have this article in their library.
Get full text

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.

Cite

CITATION STYLE

APA

Brisaboa, N. R., De Bernardo, G., Cerdeira-Pena, A., & Navarro, G. (2019). Improved compressed string dictionaries. In International Conference on Information and Knowledge Management, Proceedings (pp. 29–38). Association for Computing Machinery. https://doi.org/10.1145/3357384.3357972

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free