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Compressed full-text indexes (2007)
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| Venue: | ACM COMPUTING SURVEYS |
| Citations: | 263 - 94 self |
BibTeX
@ARTICLE{Navarro07compressedfull-text,
author = {Gonzalo Navarro and Veli Mäkinen},
title = { Compressed full-text indexes},
journal = {ACM COMPUTING SURVEYS},
year = {2007}
}
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Abstract
Full-text indexes provide fast substring search over large text collections. A serious problem of these indexes has traditionally been their space consumption. A recent trend is to develop indexes that exploit the compressibility of the text, so that their size is a function of the compressed text length. This concept has evolved into self-indexes, which in addition contain enough information to reproduce any text portion, so they replace the text. The exciting possibility of an index that takes space close to that of the compressed text, replaces it, and in addition provides fast search over it, has triggered a wealth of activity and produced surprising results in a very short time, and radically changed the status of this area in less than five years. The most successful indexes nowadays are able to obtain almost optimal space and search time simultaneously. In this paper we present the main concepts underlying self-indexes. We explain the relationship between text entropy and regularities that show up in index structures and permit compressing them. Then we cover the most relevant self-indexes up to date, focusing on the essential aspects on how they exploit the text compressibility and how they solve efficiently various search problems. We aim at giving the theoretical background to understand and follow the developments in this area.
Keyphrases
full-text index essential aspect main concept serious problem relevant self-indexes short time fast search large text collection search time successful index nowadays recent trend text compressibility compressed text length exciting possibility index structure compressed text space consumption theoretical background text portion addition contain enough information surprising result text entropy various search problem optimal space
