Luís M. S. Russo

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A compressed full-text self-index for a text T, of size u, is a data structure used to search for patterns P, of size m, in T, that requires reduced space, i.e. space that depends on the empirical entropy (H k or H 0) of T, and is, furthermore, able to reproduce any substring of T. In this paper we present a new compressed self-index able to locate the(More)
Suffix trees are by far the most important data structure in stringology, with a myriad of applications in fields like bioinformatics and information retrieval. Classical representations of suffix trees require &Theta;(<i>n</i> log <i>n</i>) bits of space, for a string of size <i>n</i>. This is considerably more than the <i>n</i> log<sub>2</sub> &sigma;(More)
A compressed full-text self-index for a text T is a data structure requiring reduced space and able to search for patterns P in T . It can also reproduce any substring of T , thus actually replacing T . Despite the recent explosion of interest on compressed indexes, there has not been much progress on functionalities beyond the basic exact search. In this(More)
Suffix trees are by far the most important data structure in stringology, with myriads of applications in fields like bioinformatics, data compression and information retrieval. Classical representations of suffix trees require O(n log n) bits of space, for a string of size n. This is considerably more than the n log 2 σ bits needed for the string itself,(More)
We present a new algorithm to calculate exact hypervolumes. Given a set of d-dimensional points, it computes the hypervolume of the dominated space. Determining this value is an important subroutine of Multiobjective Evolutionary Algorithms (MOEAs). We analyze the “Quick Hypervolume” (QHV) algorithm theoretically and experimentally. The theoretical results(More)
We study parallel and distributed compressed indexes. Compressed indexes are a new and functional way to index text strings. They exploit the compressibility of the text, so that their size is a function of the compressed text size. Moreover, they support a considerable amount of functions, more than many classical indexes. We make use of this extended(More)
Re-pair is a dictionary-based compression method invented in 1999 by J. Larsson and A. Moffat [Off-line dictionary-based compression. Proc. IEEE, 88(11):1722-1732, 2000], lacking up to now an efficiency analysis. We show that re-pair compresses a sequence T[1,n] over an alphabet of size sigma to at most 2nH<sub>k</sub> + o(n log sigma) bits, for any k =(More)
Indexing methods for the approximate string matching problem spend a considerable effort generating condensed neighborhoods. Here, we point out that condensed neighborhoods are not a minimal representation of a pattern neighborhood. We show that we can restrict our attention to super condensed neighborhoods which are minimal. We then present an algorithm(More)