Compressing integer lists with Contextual Arithmetic Trits

Fuente: arXiv
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Main Authors: Barsamian, Yann, Chailloux, André
Format: Preprint
Published: 2022
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author Barsamian, Yann
Chailloux, André
author_facet Barsamian, Yann
Chailloux, André
contents Inverted indexes allow to query large databases without needing to search in the database at each query. An important line of research is to construct the most efficient inverted indexes, both in terms of compression ratio and time efficiency. In this article, we show how to use trit encoding, combined with contextual methods for computing inverted indexes. We perform an extensive study of different variants of these methods and show that our method consistently outperforms the Binary Interpolative Method -- which is one of the golden standards in this topic -- with respect to compression size. We apply our methods to a variety of datasets and make available the source code that produced the results, together with all our datasets.
format Preprint
id arxiv_https___arxiv_org_abs_2209_02089
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Compressing integer lists with Contextual Arithmetic Trits
Barsamian, Yann
Chailloux, André
Databases
Information Theory
Inverted indexes allow to query large databases without needing to search in the database at each query. An important line of research is to construct the most efficient inverted indexes, both in terms of compression ratio and time efficiency. In this article, we show how to use trit encoding, combined with contextual methods for computing inverted indexes. We perform an extensive study of different variants of these methods and show that our method consistently outperforms the Binary Interpolative Method -- which is one of the golden standards in this topic -- with respect to compression size. We apply our methods to a variety of datasets and make available the source code that produced the results, together with all our datasets.
title Compressing integer lists with Contextual Arithmetic Trits
topic Databases
Information Theory
url https://arxiv.org/abs/2209.02089