Run-length compressed indexes are superior for highly repetitive sequence collections.(English)Zbl 1345.68124

Amir, Amihood (ed.) et al., String processing and information retrieval. 15th international symposium, SPIRE 2008, Melbourne, Australia, November 10–12, 2008. Proceedings. Berlin: Springer (ISBN 978-3-540-89096-6/pbk). Lecture Notes in Computer Science 5280, 164-175 (2008).
Summary: A repetitive sequence collection is one where portions of a base sequence of length $$n$$ are repeated many times with small variations, forming a collection of total length $$N$$. Examples of such collections are version control data and genome sequences of individuals, where the differences can be expressed by lists of basic edit operations. This paper is devoted to studying ways to store massive sets of highly repetitive sequence collections in space-efficient manner so that retrieval of the content as well as queries on the content of the sequences can be provided time-efficiently. We show that the state-of-the-art entropy-bound full-text self-indexes do not yet provide satisfactory space bounds for this specific task. We engineer some new structures that use run-length encoding and give empirical evidence that these structures are superior to the current structures.
For the entire collection see [Zbl 1154.68302].

MSC:

 68P20 Information storage and retrieval of data 68P05 Data structures 68P30 Coding and information theory (compaction, compression, models of communication, encoding schemes, etc.) (aspects in computer science)
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