Context-sensitive grammar transform: Compression and pattern matching

Shirou Maruyama, Yohei Tanaka, Hiroshi Sakamoto, Masayuki Takeda

Research output: Contribution to journalConference articlepeer-review

10 Citations (Scopus)

Abstract

A framework of context-sensitive grammar transform is proposed. A greedy compression algorithm with the transform model is presented as well as a Knuth-Morris-Pratt (KMP)-type compressed pattern matching (CPM) algorithm. The compression performance is a match for gzip and Re-Pair. The search speed of our CPM algorithm is almost twice faster than the KMP type CPM algorithm on Byte-Pair-Encoding by Shibata et al. (2000), and in the case of short patterns, faster than the Boyer-Moore-Horspool algorithm with the stopper encoding by Rautio et al. (2002), which is regarded as one of the best combinations that allows a practically fast search.

Original languageEnglish
Pages (from-to)27-38
Number of pages12
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5280 LNCS
DOIs
Publication statusPublished - 2008
Event15th International Symposium on String Processing and Information Retrieval, SPIRE 2008 - Melbourne. VIC, Australia
Duration: Nov 10 2008Nov 12 2008

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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