Content Selection Operators for Multidocument Summarization Based on Cross-Document Structure Theory

M. L. C. Jorge, T. Pardo
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引用次数: 6

Abstract

This paper aims at presenting an analysis of content selection techniques for multidocument summarization based on the multidocument discourse theory CST (Cross-document Structure Theory). We approach the task of content selection by using CST-based operators and focus specifically on redundancy treatment, which is an important and pervasive problem in multidocument summarization. Our experiments with Brazilian Portuguese news texts show that CST improves summaries quality by exploring relations among texts. Particularly, redundancy is reduced by identifying common information among texts, especially when compression rate is low.
基于跨文档结构理论的多文档摘要内容选择算子
本文旨在分析基于跨文档结构理论(CST)的多文档摘要内容选择技术。我们通过使用基于cst的算子来完成内容选择任务,并特别关注冗余处理,这是多文档摘要中一个重要且普遍存在的问题。我们对巴西葡萄牙语新闻文本的实验表明,CST通过探索文本之间的关系来提高摘要质量。特别是,通过识别文本之间的公共信息来减少冗余,特别是在压缩率较低的情况下。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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