Generic technologies for single- and multi-document summarization |
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| Affiliation: | 1. Department of Emergency Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, PR China;2. Department of Intensive Care Unit, The First Affiliated Hospital of Henan University of TCM, Zhengzhou, PR China;1. Division of Mood Disorders, Shanghai Clinical Center for Mental Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, P.R. China;2. Division of Mood Disorders, Hongkou District Mental Health Center of Shanghai, Shanghai, P.R. China;3. Institute of Mental Health, Peking University, Beijing, P.R. China;4. Mental Health Institute, The Second Xiangya Hospital of Central South University, Changsha, Hunan, P.R. China;5. Shanghai Key Laboratory of Forensic Medicine, Institute of Forensic Science, Ministry of Justice, Shanghai, P.R. China |
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| Abstract: | The technologies for single- and multi-document summarization that are described and evaluated in this article can be used on heterogeneous texts for different summarization tasks. They refer to the extraction of important sentences from the documents, compressing the sentences to their essential or relevant content, and detecting redundant content across sentences. The technologies are tested at the Document Understanding Conference, organized by the National Institute of Standards and Technology, USA in 2002 and 2003. The system obtained good to very good results in this competition. We tested our summarization system also on a variety of English Encyclopedia texts and on Dutch magazine articles. The results show that relying on generic linguistic resources and statistical techniques offer a basis for text summarization. |
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