Authors
Michel Gagnon, Lyne Da Sylva
Publication date
2006
Conference
Advances in Artificial Intelligence: 19th Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2006, Québec City, Québec, Canada, June 7-9, 2006. Proceedings 19
Pages
312-323
Publisher
Springer Berlin Heidelberg
Description
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.
Total citations
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Scholar articles
M Gagnon, L Da Sylva - Advances in Artificial Intelligence: 19th Conference of …, 2006