Similarity-based Multilingual Multi-Document Summarization
- Similarity-based Multilingual Multi-Document Summarization
- Evans, David Kirk
Klavans, Judith L.
- Computer Science
- Persistent URL:
- Columbia University Computer Science Technical Reports
- Part Number:
- Department of Computer Science, Columbia University
- Publisher Location:
- New York
- We present a new approach for summarizing clusters of documents on the same event, some of which are machine translations of foreign-language documents and some of which are English. Our approach to multilingual multi-document summarization uses text similarity to choose sentences from English documents based on the content of the machine translated documents. A manual evaluation shows that 68\% of the sentence replacements improve the summary, and the overall summarization approach outperforms first-sentence extraction baselines in automatic ROUGE-based evaluations.
- Computer science
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- Suggested Citation:
- David Kirk Evans, Kathleen McKeown, Judith L. Klavans, 2005, Similarity-based Multilingual Multi-Document Summarization, Columbia University Academic Commons, https://doi.org/10.7916/D8K362H5.