Using Bilingual Information for Cross-Language Document Summarization

Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics, pages 1546–1555, Portland, Oregon, June 19-24, 2011. c⃝2011 Association for Computational Linguistics Using Bilingual Information for Cross-Language Document Summarization Xiaojun Wan Institute of Compute Science and Technology, Peking University, Beijing 100871, China Key Laboratory of Computational Linguistics (Peking University), MOE, China wanxiaojun@icst.pku.edu.cn Abstract Cross-language document summarization is de- fined as the task of producing a summary in a target language (e.g. Chinese) for a set of documents in a source language (e.g. English). Existing methods for addressing this task make use of either the information from the original documents in the source language or the infor- mation from the translated documents in the target language. In this study, we propose to use the bilingual information from both the source and translated documents for this task. Two summarization methods (SimFusion and CoRank) are proposed to leverage the bilingual information in the graph-based ranking frame- work for cross-language summary extraction. Experimental results on the DUC2001 dataset with manually translated reference Chinese summaries show the effectiveness of the pro- posed methods. 1 Introduction Cross-language document summarization is de- fined as the task of producing a summary in a dif- ferent target language for a set of documents in a source language (Wan et al., 2010). In this study, we focus on English-to-Chinese cross-language summarization, which aims to produce Chinese summaries for English document sets. The task is very useful in the field of multilingual information access. For example, it is beneficial for most Chi- nese readers to quickly browse and understand English news documents or document sets by read- ing the corresponding Chinese summaries. A few pilot studies have investigated the task in recent years and exiting methods make use of ei- ther the information in the source language or the information in the target language after using ma- chine translation. In particular, for the task of Eng- lish-to-Chinese cross-language summarization, one method is to directly extract English summary sen- tences based on English features extracted from the English documents, and then automatically trans- late the English summary sentences into Chinese summary sentences. The other method is to auto- matically translate the English sentences into Chi- nese sentences, and then directly extract Chinese summary sentences based on Chinese features. The two methods make use of the information from only one language side. However, it is not very reliable to use only the information in one language, because the machine translation quality is far from satisfactory, and thus the translated Chinese sentences usually contain some errors and noises. For example, the English sentence “Many destroyed power lines are thought to be uninsured, as are trees and shrubs uprooted across a wide area.” is automatically translated into the Chinese sentence “许多破坏电源线被认 为是保险的，因为是连根拔起的树木和灌木， 在广泛的领域。” by using Google Translate1 , but the Chinese sentence contains a few translation errors. Therefore, on the one side, if we rely only on the English-side information to extract Chinese 1 http://translate.google.com/. Note that the translation service is updated frequently …

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