Shirou Maruyama

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Grammar-based compression is a well-studied technique for constructing a small context-free grammar (CFG) uniquely deriving a given text. In this paper, we present an online algorithm for lightweight grammar-based compression. Our algorithm is based on the LCA algorithm [Sakamoto et al. 2004]which guarantees nearly optimum compression ratio and space. LCA,(More)
A space-efficient approximation algorithm for the grammar-based compression problem, which requests for a given string to find a smallest context-free grammar deriving the string, is presented. For the input length n and an optimum CFG size g, the algorithm consumes only O(g log g) space and O(n log∗n) time to achieve O((log∗n) logn) approximation ratio to(More)
We present novel variants of fully online LCA (FOLCA), a fully online grammar compression that builds a straight line program (SLP) and directly encodes it into a succinct representation in an online manner. FOLCA enables a direct encoding of an SLP into a succinct representation that is asymptotically equivalent to an information theoretic lower bound for(More)
We consider the problem of restructuring compressed texts without explicit decompression. We present algorithms which allow conversions from compressed representations of a string T produced by any grammar-based compression algorithm, to representations produced by several specific compression algorithms including LZ77, LZ78, run length encoding, and some(More)
A searchable data structure for the edit-sensitive parsing (ESP) is proposed. Given a string S, its ESP tree is equivalent to a context-free grammar G generating just S, which is represented by a DAG. Using the succinct data structures for trees and permutations, G is decomposed to two LOUDS bit strings and single array in (1+ε)n log n+ 4n+o(n) bits for any(More)
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