A Multi-Document Summarization Approach based on Hierarchical Clustering of Documents: Extracting both Commonality and Specificity of Documents

Anonymous

Abstract: The multi-document summarization task requires the designed summarizer to generate a short text that covers the important information of original documents and satisfies content diversity. This paper proposes a multi-document summarization approach based on hierarchical clustering of documents. It utilizes the constructed class tree of documents to extract both the sentences reflecting the commonality of all documents and the sentences reflecting the specificity of some subclasses of these documents for generating the summary, so as to satisfy the coverage and diversity requirements of multi-document summarization. Comparative experiments on DUC'2002-2004 datasets prove the effectiveness of considering both the commonality and specificity of documents for multi-document summarization. And the experiments on DUC'2004 and Multi-News datasets show that our approach achieves competitive performance compared to the state-of-the-art unsupervised and supervised approaches.

Paper Type: long