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The smallest grammar problem revisited

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abstract

In a seminal paper of Charikar et al. on the smallest grammar problem, the authors derive upper and lower bounds on the approximation ratios for several grammar-based compressors, but in all cases there is a gap between the lower and upper bound. Here the gaps for $\mathsf{LZ78}$ and $\mathsf{BISECTION}$ are closed by showing that the approximation ratio of $\mathsf{LZ78}$ is $\Theta( (n/\log n)^{2/3})$, whereas the approximation ratio of $\mathsf{BISECTION}$ is $\Theta(\sqrt{n/\log n})$. In addition, the lower bound for $\mathsf{RePair}$ is improved from $\Omega(\sqrt{\log n})$ to $\Omega(\log n/\log\log n)$. Finally, results of Arpe and Reischuk relating grammar-based compression for arbitrary alphabets and binary alphabets are improved.

fields

cs.DS 1

years

2019 1

verdicts

REJECT 1

representative citing papers

Re-Pair In Small Space

cs.DS · 2019-08-14 · reject · novelty 7.0

A new algorithm computes Re-Pair, a grammar-based compression method, in O(n^2) time using roughly text-sized working space, but the core frequency-counting proof appears to overcount repeated-character bigrams.

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  • Re-Pair In Small Space cs.DS · 2019-08-14 · reject · none · ref 2 · internal anchor

    A new algorithm computes Re-Pair, a grammar-based compression method, in O(n^2) time using roughly text-sized working space, but the core frequency-counting proof appears to overcount repeated-character bigrams.