2005 Reports
Similarity-based Multilingual Multi-Document Summarization
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.
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Files
- cucs-014-05.pdf application/pdf 188 KB Download File
More About This Work
- Academic Units
- Computer Science
- Publisher
- Department of Computer Science, Columbia University
- Series
- Columbia University Computer Science Technical Reports, CUCS-014-05
- Published Here
- April 26, 2011