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相似度质心多层过滤策略的动态文摘方法

DOI: 10.3969/j.issn.1006-7043.201309080

Keywords: 动态文摘模型, 质心整体选优, 相似度累加模型

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Abstract:

为了研究网络快速有效获取信息的方法,网络动态演化内容的识别和分析成为人们迫切需要解决的关键问题。动态多文档文摘建立在时间信息基础上,从网络数据的动态性能入手,对同一主题不同时段的文摘集合进行分析,在识别信息内容差异性的基础上,对信息的动态演化性进行建模。在提出相似度累加模型基础上,进一步提出了基于质心整体选优的动态文摘模型。分析当前文档集合与历史集合强关联性,以选择出的不同文摘句为首句生成候选文摘集合,然后根据质心多层过滤优选方法从中选出最优文摘结果。这种模型方法消除了因首句选择不当而对文摘性能造成的影响,在国际标准评测Taxt Anynasis Conference 2008的Update task任务语料上进行了测试,并且获得了较好的实验结果。

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