EUSUM: extracting easy-to-understand english summaries for non-native readers

  • Authors:

  • Xiaojun Wan;Huiying Li;Jianguo Xiao

  • Affiliations:

  • Peking University, Beijing, China;Peking University, Beijing, China;Peking University, Beijing, China

  • Venue:
  • Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
  • Year:
  • 2010

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Abstract

In this paper we investigate a novel and important problem in multi-document summarization, i.e., how to extract an easy-to-understand English summary for non-native readers. Existing summarization systems extract the same kind of English summaries from English news documents for both native and non-native readers. However, the non-native readers have different English reading skills because they have different English education and learning backgrounds. An English summary which can be easily understood by native readers may be hardly understood by non-native readers. We propose to add the dimension of reading easiness or difficulty to multi-document summarization, and the proposed EUSUM system can produce easy-to-understand summaries according to the English reading skills of the readers. The sentence-level reading easiness (or difficulty) is predicted by using the SVM regression method. And the reading easiness score of each sentence is then incorporated into the summarization process. Empirical evaluation and user study have been performed and the results demonstrate that the EUSUM system can produce more easy-to-understand summaries for non-native readers than existing summarization systems, with very little sacrifice of the summary's informativeness.