Optimal Parsing for dictionary text compression
type: Dataset
description: Dictionary-based compression algorithms include a parsing strategy to transform the input text into a sequence of dictionary phrases. Given a text, such process usually is not unique and, for compression purpose, it makes sense to find one of the possible parsing that minimizes the final compression ratio. This is the parsing problem. An optimal parsing is a parsing strategy or a parsing algorithm that solve the parsing problem taking account of all the constraints of a compression algorithm or of a class of homogeneous compression algorithms. Compression algorithm constrains are, for instance, the dictionary itself, i.e. the dynamic set of available phrases, and how much a phrase weight on the compressed text, i.e. the length of the codeword that represent such phrase also denoted as the cost of a dictionary pointer encoding. In more than 30th years of history of dictionary based text compression, while plenty of algorithms, variants and extensions appeared and while such approach to text compression become one of the most appreciated and utilized in almost all the storage and communication process, only few optimal parsing algorithms was presented. Many compression algorithms still leaks optimality of their parsing or, at least, proof of optimality. This happens because there is not a general model of the parsing problem that includes all the dictionary based algorithms and because the existing optimal parsings work under too restrictive hypothesis. This work focus on the parsing problem and presents both a general model for dictionary based text compression called Dictionary-Symbolwise theory and a general parsing algorithm that is proved to be optimal under some realistic hypothesis. This algorithm is called Dictionary-Symbolwise ￼Flexible Parsing and it covers almost all the cases of dictionary based text compression algorithms together with the large class of their variants where the text is decomposed in a sequence of symbols and dictionary phrases.In this wo…
landing page: https://theses.hal.science/tel-00804215
identifier: NNT: 2012PEST1091
keyword: compression-du-texte
keyword: compression-par-dictionnaire
keyword: dictionary-compression
keyword: infoeu-reposemanticsdoctoralthesis
keyword: infoinfo-ohcomputer-science-csother-csoh
keyword: optimal-parsing
keyword: parsing-optimal
keyword: text-compression
keyword: theses
issued: 2026-05-12T04:35:55.576246
modified: 2026-05-12T04:35:55.576253
language: en
contact point: Organization
  fn: CCSD

test_moissonnage_selune
type: Agent

Optimal Parsing for dictionary text compression
type: Distribution
format: HTML
access URL: https://theses.hal.science/tel-00804215
issued: 2026-05-12T04:35:55.582432
modified: 2026-05-12T04:35:55.553837