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このアイテムの引用には次の識別子を使用してください: http://hdl.handle.net/10119/8397

タイトル: Approach to scalable statistical text summarization
著者: Nguyen, Minh Le
Horiguchi, Susumu
発行日: 2002-06-27
出版者: 北陸先端科学技術大学院大学情報科学研究科
誌名: Research report (School of Information Science, Japan Advanced Institute of Science and Technology)
巻: IS-RR-2002-016
開始ページ: 1
終了ページ: 16
抄録: This paper analysts some aspect of applying statistical machine translation method to summary text document. After considering this text summarization as statistical machine translation system we apply translation model to test on a corpus consist of long sentence and its reduced, which was produced from our decomposition program. We also revised several translation model and language model to discover a fix model for text summarization. After using training algorithm to cope with corpus, the most important in the remainder is complexity of decoder, for this reason, we will discuss the hierarchy of parallel algorithm for both training data and decoder process is essential.
URI: http://hdl.handle.net/10119/8397
資料タイプ: publisher


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