Approximating LZ77 via Small-Space Multiple-Pattern Matching

April 24, 2015 Β· Declared Dead Β· πŸ› Embedded Systems and Applications

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Authors Johannes Fischer, Travis Gagie, PaweΕ‚ Gawrychowski, Tomasz Kociumaka arXiv ID 1504.06647 Category cs.DS: Data Structures & Algorithms Citations 36 Venue Embedded Systems and Applications Last Checked 3 months ago
Abstract
We generalize Karp-Rabin string matching to handle multiple patterns in $\mathcal{O}(n \log n + m)$ time and $\mathcal{O}(s)$ space, where $n$ is the length of the text and $m$ is the total length of the $s$ patterns, returning correct answers with high probability. As a prime application of our algorithm, we show how to approximate the LZ77 parse of a string of length $n$. If the optimal parse consists of $z$ phrases, using only $\mathcal{O}(z)$ working space we can return a parse consisting of at most $(1+\varepsilon)z$ phrases in $\mathcal{O}(\varepsilon^{-1}n\log n)$ time, for any $\varepsilon\in (0,1]$. As previous quasilinear-time algorithms for LZ77 use $Ξ©(n/\textrm{polylog }n)$ space, but $z$ can be exponentially small in $n$, these improvements in space are substantial.
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