DocumentCode
2049257
Title
An Online Algorithm for Lightweight Grammar-Based Compression
Author
Maruyama, Shirou ; Takeda, Masayuki ; Nakahara, Masaya ; Sakamoto, Hiroshi
Author_Institution
Dept. of Inf., Kyushu Univ., Fukuoka, Japan
fYear
2011
fDate
21-24 June 2011
Firstpage
19
Lastpage
28
Abstract
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, however, is an offline algorithm and requires external space to save space consumption. Therefore, we present its online version which inherits most characteristics of the original LCA. Our algorithm guarantees O(log2 n)-approximation ratio for an optimum grammar size, and all work is carried out on a main memory space which is bounded by the output size. In addition, we propose more practical encoding based on parentheses representation of a binary tree. Experimental results for repetitive texts demonstrate that our algorithm achieves effective compression compared to other practical compressors and the space consumption of our algorithm is smaller than the input text size.
Keywords
approximation theory; computational complexity; context-free grammars; data compression; LCA algorithm; O(log2 n)-approximation ratio; context-free grammar; lightweight grammar-based compression; online algorithm; Approximation algorithms; Approximation methods; Compressors; Dictionaries; Grammar; Production; Vegetation; approximation algorithm; grammar-based compression; lossless compression; online algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Compression, Communications and Processing (CCP), 2011 First International Conference on
Conference_Location
Palinuro
Print_ISBN
978-1-4577-1458-0
Electronic_ISBN
978-0-7695-4528-8
Type
conf
DOI
10.1109/CCP.2011.40
Filename
6061023
Link To Document