Multi-document Relationship Model for a same subject and its application in automatic summarization

Hao Bai, De-xiang Zhou
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Abstract

In this paper, we proposed Multi-document Relationship Model for a same subject and applicated it in automatic summarization. By using the relationship between text units in different level and information of time and sequence of event contained into document set, this model fuse many documents to extract summarization automatically under not reducing the information in original documents. This model simplied the triditional model presented by cross structure theory and simultaneously, replenish the evolution and distribution information of subject which lacked in information fusion. This paper gives some algorithm about construction of the model, information fusion for multi-document and summarization extraction and so on. Experiment results implied that the model proposed in this paper can solve the problem of summarization extraction for multi-document very well.
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同一主题的多文档关系模型及其在自动摘要中的应用
本文提出了同一主题的多文档关系模型,并将其应用于自动摘要中。该模型利用不同层次的文本单元之间的关系以及文档集中所包含的时间和事件顺序信息,在不减少原始文档信息的前提下,融合多篇文档自动提取摘要。该模型简化了交叉结构理论提出的传统模型,同时补充了信息融合中缺乏的主体演化和分布信息。本文给出了模型构建、多文档信息融合、摘要提取等算法。实验结果表明,本文提出的模型可以很好地解决多文档摘要抽取问题。
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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