自动汇总
计算机科学
情报检索
多文档摘要
突出
自然语言处理
人工智能
作者
Chao Zhao,Teng-Hao Huang,Somnath Basu Roy Chowdhury,Muthu Kumar Chandrasekaran,Kathleen R. McKeown,Snigdha Chaturvedi
标识
DOI:10.18653/v1/2022.findings-acl.51
摘要
A common method for extractive multi-document news summarization is to re-formulate it as a single-document summarization problem by concatenating all documents as a single meta-document. However, this method neglects the relative importance of documents. We propose a simple approach to reorder the documents according to their relative importance before concatenating and summarizing them. The reordering makes the salient content easier to learn by the summarization model. Experiments show that our approach outperforms previous state-of-the-art methods with more complex architectures.
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