Learning Sentence Reduction Rules for Brazilian Portuguese

Abstract

We present in this paper a method for sentence reduction with summarization purposes. The task is modeled as a machine learning problem, relying on shallow and linguistic features, in order to automatically learn symbolic patterns/rules that produce good sentence reductions. We evaluate our results with Brazilian Portuguese texts and show that we achieve high accuracy and produce better results than the existing solution for this language.