Text Compression by Syntactic Pruning

  • Michel Gagnon
  • Lyne Da Sylva
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4013)


We present a method for text compression, which relies on pruning of a syntactic tree. The syntactic pruning applies to a complete analysis of sentences, performed by a French dependency grammar. Sub-trees in the syntactic analysis are pruned when they are labelled with targeted relations. Evaluation is performed on a corpus of sentences which have been manually compressed. The reduction ratio of extracted sentences averages around 70%, while retaining grammaticality or readability in a proportion of over 74%. Given these results on a limited set of syntactic relations, this shows promise for any application which requires compression of texts, including text summarization.


Phrase Structure Sentence Length Prepositional Phrase Syntactic Analysis Subordinate Clause 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Michel Gagnon
    • 1
  • Lyne Da Sylva
    • 2
  1. 1.Département de génie informatiqueÉcole Polytechnique de MontréalCanada
  2. 2.École de bibliothéconomie et des sciences de l’informationUniversité de MontréalCanada

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