基于上下文的波斯语多文档摘要(全局视图)

Asef Poormasoomi, M. Kahani, Saeed Varasteh Yazdi, Hossein Kamyar
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引用次数: 8

摘要

多文档摘要是从同一主题的多个文档中自动提取信息。本文提出了一种新的方法,利用LSA提取主题的全局上下文,并利用SRL和WordNet语义相似度去除波斯语的句子冗余。在以前的方法中,重点是句子特征(局部视图)作为文本的主要和基本单位。在本文中,基于隐藏在一个主题的所有文档中的主要上下文来选择句子。实验结果表明,该方法优于其他波斯语多文档系统。
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Context-Based Persian Multi-document Summarization (Global View)
Multi-document summarization is the automatic extraction of information from multiple documents of the same topic. This paper proposes a new method, using LSA, for extracting the global context of a topic and removes sentence redundancy using SRL and WordNet semantic similarity for Persian language. In the previous approaches, the focus was on the sentence features (local view) as the main and basic unit of text. In this paper, the sentences are selected based on the main context hidden in the all documents of a topic. The experimental results show that our proposed method outperforms other Persian multi-document systems.
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