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The University of Alicante at MultiLing 2015: approach, results and further insights

机译:2015年多营机构的阿利坎特大学:方法,结果和进一步见解

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In this paper we present the approach and results of our participation in the 2015 MultiLing Single-document Summarization task. Our approach is based on the Principal Component Analysis (PCA) technique enhanced with lexical-semantic knowledge. For testing our approach, different configurations were set up, thus generating different types of summaries (i.e., generic and topic-focused), as well as testing some language-specific resources on top of the language-independent basic PCA approach, submitting a total of 6 runs for each selected language (English, German, and Spanish). Our participation in MultiLing has been very positive, ranking at intermediate positions when compared to the other participant systems, showing that PCA is a good technique for generating language-independent summaries, but the addition of lexical-semantic knowledge may heavily depend on the size and quality of the resources available for each language.
机译:在本文中,我们介绍了我们参与2015年多营单一文件摘要任务的方法和结果。我们的方法是基于具有词汇语义知识增强的主要成分分析(PCA)技术。为了测试我们的方法,建立了不同的配置,从而生成不同类型的摘要(即,通用和主题),以及在语言无关的基本PCA方法之上测试某些语言特定的资源,提交总计每种选定语言的6个运行(英语,德语和西班牙语)。我们的参与多营管道已经非常积极,在与其他参与者系统相比时,在中间位置排名,表明PCA是一种用于生成独立于语言的摘要的良好技术,但添加词汇语义知识可能会严重取决于尺寸和可用于每种语言的资源质量。

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