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    秦 兵 刘 挺 陈尚林 李 生. 多文档文摘中句子优化选择方法研究[J]. 计算机研究与发展, 2006, 43(6): 1129-1134.
    引用本文: 秦 兵 刘 挺 陈尚林 李 生. 多文档文摘中句子优化选择方法研究[J]. 计算机研究与发展, 2006, 43(6): 1129-1134.
    Qin Bing, Liu Ting, Chen Shanglin, and Li Sheng. Sentences Optimum Selection for Multi-Document Summarization[J]. Journal of Computer Research and Development, 2006, 43(6): 1129-1134.
    Citation: Qin Bing, Liu Ting, Chen Shanglin, and Li Sheng. Sentences Optimum Selection for Multi-Document Summarization[J]. Journal of Computer Research and Development, 2006, 43(6): 1129-1134.

    多文档文摘中句子优化选择方法研究

    Sentences Optimum Selection for Multi-Document Summarization

    • 摘要: 在多文档文摘子主题划分的基础上,提出了一种在子主题之间对文摘句优化选择的方法.首先在句子相似度计算的基础上,形成多文档集合的子主题,通过对各子主题打分,确定子主题的抽取顺序.以文摘中有效词的覆盖率作为优化指标,在各个子主题中选择文摘句.从减少子主题之间及子主题内部的信息的冗余性两个角度选择文摘句,使文摘的信息覆盖率得到很大提高.实验表明,生成的文摘是令人满意的.

       

      Abstract: An approach for sentence optimum selection based on sub-topics of multi-documents is proposed. Multi-documents can be clustered into sub-topics after sentence similarity calculation, which can be sorted by scoring. Then sentences from all sub-topics are selected in order to get maximum coverage ratio of effective words. Using this method, the information redundancy of each sub-topic and among sub-topics is reduced. The information coverage ratio of the summarization is better improved. The experiment shows that the result is satisfied.

       

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