Investigating Machine Learning Approaches for Sentence Compression in Different Application Contexts for Portuguese

被引：4

作者：

Asevedo Nobrega, Fernando Antonio ^{[1
]}

Salgueiro Pardo, Thiago Alexandre ^{[1
]}

机构：

[1] Univ Sao Paulo, Inst Math & Comp Sci, Interinst Ctr Computat Linguist NILC, Sao Carlos, SP, Brazil

来源：

COMPUTATIONAL PROCESSING OF THE PORTUGUESE LANGUAGE (PROPOR 2016) | 2016年 / 9727卷

关键词：

D O I：

10.1007/978-3-319-41552-9_25

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Sentence compression aims to produce a shorter version of an input sentence and it is very useful for many Natural Language applications. However, investigations in this field are frequently task focused and for English language. In this paper, we report machine learning approaches to compress sentences in Portuguese. We analyze different application contexts and the available features. Our experiments produce good results, outperforming some previously investigated approaches.

引用

页码：245 / 250

页数：6

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