Title
Computing Convolution on Grammar-Compressed Text
Abstract
The convolution between a text string $S$ of length $N$ and a pattern string $P$ of length $m$ can be computed in $O(N \log m)$ time by FFT. It is known that various types of approximate string matching problems are reducible to convolution. In this paper, we assume that the input text string is given in a compressed form, as a straight-line program (SLP), which is a context free grammar in the Chomsky normal form that derives a single string. Given an SLP $\mathcal{S}$ of size $n$ describing a text $S$ of length $N$, and an uncompressed pattern $P$ of length $m$, we present a simple $O(nm \log m)$-time algorithm to compute the convolution between $S$ and $P$. We then show that this can be improved to $O(\min\{nm, N-\alpha\} \log m)$ time, where $\alpha \geq 0$ is a value that represents the amount of redundancy that the SLP captures with respect to the length-$m$ substrings. The key of the improvement is our new algorithm that computes the convolution between a trie of size $r$ and a pattern string $P$ of length $m$ in $O(r \log m)$ time.
Year
DOI
Venue
2013
10.1109/DCC.2013.53
data compression conference
Keywords
DocType
Volume
slp capture,pattern string,chomsky normal form,text string,uncompressed pattern,computing convolution,time algorithm,input text string,approximate string,single string,log m,grammar-compressed text,convolution,pattern matching,slp,vectors,text analysis,context free grammars,context free grammar,grammar,string matching,computational complexity,data compression
Conference
abs/1303.3945
ISSN
Citations 
PageRank 
1068-0314
2
0.37
References 
Authors
14
5
Name
Order
Citations
PageRank
Toshiya Tanaka120.37
Tomohiro I214822.06
Shunsuke Inenaga359579.02
Hideo Bannai462079.87
Masayuki Takeda590279.24