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Training Parse Trees for Efficient VF Coding

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Title: Training Parse Trees for Efficient VF Coding
Authors: Uemura, Takashi Browse this author
Yoshida, Satoshi Browse this author
Kida, Takuya Browse this author →KAKEN DB
Asai, Tatsuya Browse this author
Okamoto, Seishi Browse this author
Issue Date: 2010
Publisher: Springer Berlin / Heidelberg
Citation: String Processing and Information Retrieval : 17th International Symposium, SPIRE 2010, Los Cabos, Mexico, October 11-13, 2010. Proceedings (Lecture Notes in Computer Science; 6393), 2010, pp.179-184, ISBN: 978-3-642-16320-3, ISSN: 0302-9743, E-ISSN: 1611-3349
Publisher DOI: 10.1007/978-3-642-16321-0_17
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.
Rights: The original publication is available at
Type: bookchapter (author version)
Appears in Collections:情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

Submitter: 喜田 拓也

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