8,323 research outputs found

    Compressed Representations of Permutations, and Applications

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    We explore various techniques to compress a permutation π\pi over n integers, taking advantage of ordered subsequences in π\pi, while supporting its application π\pi(i) and the application of its inverse π−1(i)\pi^{-1}(i) in small time. Our compression schemes yield several interesting byproducts, in many cases matching, improving or extending the best existing results on applications such as the encoding of a permutation in order to support iterated applications πk(i)\pi^k(i) of it, of integer functions, and of inverted lists and suffix arrays

    LRM-Trees: Compressed Indices, Adaptive Sorting, and Compressed Permutations

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    LRM-Trees are an elegant way to partition a sequence of values into sorted consecutive blocks, and to express the relative position of the first element of each block within a previous block. They were used to encode ordinal trees and to index integer arrays in order to support range minimum queries on them. We describe how they yield many other convenient results in a variety of areas, from data structures to algorithms: some compressed succinct indices for range minimum queries; a new adaptive sorting algorithm; and a compressed succinct data structure for permutations supporting direct and indirect application in time all the shortest as the permutation is compressible.Comment: 13 pages, 1 figur

    Compressed Spaced Suffix Arrays

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    Spaced seeds are important tools for similarity search in bioinformatics, and using several seeds together often significantly improves their performance. With existing approaches, however, for each seed we keep a separate linear-size data structure, either a hash table or a spaced suffix array (SSA). In this paper we show how to compress SSAs relative to normal suffix arrays (SAs) and still support fast random access to them. We first prove a theoretical upper bound on the space needed to store an SSA when we already have the SA. We then present experiments indicating that our approach works even better in practice
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