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Text Compression by Syntactic Pruning

机译:通过语法修剪压缩文本

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摘要

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.
机译:我们提出了一种文本压缩方法,该方法依赖于语法树的修剪。语法修剪适用于由法语依存语法执行的句子的完整分析。语法分析中的子树被标记为目标关系时,它们会被修剪。对已被手动压缩的句子的语料库进行评估。提取句子的平均减少率约为70%,同时保留超过74%的语法或可读性。鉴于这些结果基于一组有限的句法关系,这表明它对需要压缩文本(包括文本摘要)的任何应用程序都具有希望。

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