Training parse trees for efficient VF coding

Authors:
Takashi Uemura;Satoshi Yoshida;Takuya Kida;Tatsuya Asai;Seishi Okamoto
Affiliations:
Hokkaido University, Sapporo, Japan;Hokkaido University, Sapporo, Japan;Hokkaido University, Sapporo, Japan;Fujitsu Laboratories Ltd., Kawasaki, Japan;Fujitsu Laboratories Ltd., Kawasaki, Japan
Venue:
SPIRE'10 Proceedings of the 17th international conference on String processing and information retrieval
Year:
2010

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Abstract

We address the problem of improving variable-length-to-fixed-length codes (VF codes), which have favourable properties for fast compressed pattern matching but moderate compression ratios. Compression ratio of VF codes depends on the parse tree that is used as a dictionary. We propose a method that trains a parse tree by scanning an input text repeatedly, and we show experimentally that it improves the compression ratio of VF codes rapidly to the level of state-of-the-art compression methods.