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Title Rank/Select on Dynamic Compressed Sequences and Applications
Authors Rodrigo González, Gonzalo Navarro
Publication date October 2009
Abstract Operations $rank$ and $select$ over a sequence of symbols have many
applications to the design of succinct and compressed data structures
managing text collections, structured text, binary relations, trees, graphs, and
so on. We are interested in the case where the collections can be updated via
insertions and deletions of symbols. Two current solutions stand out as the
best in the tradeoff of space versus time (when considering all the operations).
One solution, by Mäkinen and Navarro, achieves compressed space (i.e.,
$nH_0+o(n\log\sigma)$ bits) and $O(\log n \log \sigma)$ worst-case time for
all the operations, where $n$ is the sequence length, $\sigma$ is the alphabet
size, and $H_0$ is the zero-order entropy of the sequence. The other solution,
by Lee and Park, achieves $O(\log n (1+\frac{\log \sigma}{\log\log n}))$
amortized time and uncompressed space, i.e. $n\log_2\sigma +O(n)+o(n\log\sigma)$
bits. In this paper we show that the best of both worlds can be achieved. We
combine the solutions to obtain $nH_0+o(n\log\sigma)$ bits of space and
$O(\log n (1+\frac{\log \sigma}{\log\log n}))$ worst-case time for all the
operations. Apart from the best current solution to the problem, we obtain
several byproducts of independent interest applicable to partial sums, text
indexes, suffix arrays, the Burrows-Wheeler transform, and others.
Pages 4414-4422
Volume 410
Journal name Theoretical Computer Science
Publisher Elsevier Science (Amsterdam, The Netherlands)
Reference URL View reference page