将词汇语义知识纳入主成分分析技术对多语言摘要生成的影响研究

IF 0.3 Q4 LINGUISTICS
Linguamatica Pub Date : 2015-07-31 DOI:10.21814/LM.7.1.205
Óscar Alcón, E. Lloret
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引用次数: 3

摘要

自动文本摘要的目标是降低保存相关信息的文本的维数。在本文中,我们分析并应用了独立于语言的主成分分析技术来生成抽取的单文档多语言摘要。本文将通过语言相关的资源和工具来研究该技术在添加和不添加词汇语义知识的情况下的性能。实验使用了两种不同的语料库:三种语言(英语、德语和西班牙语)的新闻专线和维基百科文章,以验证该技术在几种情况下的使用。与现有的多语文系统相比,拟议的方法显示出非常有竞争力的结果,这表明,虽然在技术和要考虑的知识类型方面仍有改进的余地,但这在其他情况和其他语文方面具有很大的应用潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estudio de la influencia de incorporar conocimiento léxico-semántico a la técnica de Análisis de Componentes Principales para la generación de resúmenes multilingües
The objective of automatic text summarization  is to reduce the dimension of a text keeping the relevant information. In this paper we analyse and apply the language-independent Principal Component Analysis technique for generating extractive single-document multilingual summaries. This technique will be studied to evaluate its performance with and without adding lexical-semantic knowledge through language-dependent resources and tools. Experiments were conducted using two different corpora: newswire and Wikipedia articles in three languages (English, German and Spanish) to validate the use of this technique in several scenarios. The proposed approaches show very competitive results compared to multilingual available systems, indicating that, although there is still room for improvement with respect to the technique and the type of knowledge to be taken into consideration, this has great potential for being applied in other contexts and for other languages.
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来源期刊
Linguamatica
Linguamatica LINGUISTICS-
CiteScore
1.40
自引率
0.00%
发文量
4
审稿时长
6 weeks
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