The task of cross-language document summarization is to create a summary in a target language from documents in a different source language. Previous methods only involve direct extraction of automatically translated sentences from the original documents. Inspired by phrasebased machine translation, we propose a phrase-based model to simultaneously perform sentence scoring, extraction and compression. We design a greedy algorithm to approximately optimize the score function. Experimental results show that our methods outperform the state-of-theart extractive systems while maintaining similar grammatical quality.
Phrase-based Compressive Cross-Language Summarization
Jin-ge Yao,Xiaojun Wan,Jianguo Xiao
Published 2015 in Conference on Empirical Methods in Natural Language Processing
ABSTRACT
PUBLICATION RECORD
- Publication year
2015
- Venue
Conference on Empirical Methods in Natural Language Processing
- Publication date
2015-09-01
- Fields of study
Linguistics, Computer Science
- Identifiers
- External record
- Source metadata
Semantic Scholar
CITATION MAP
EXTRACTION MAP
CLAIMS
- No claims are published for this paper.
CONCEPTS
- No concepts are published for this paper.
REFERENCES
Showing 1-22 of 22 references · Page 1 of 1
CITED BY
Showing 1-57 of 57 citing papers · Page 1 of 1