Dynamic Multi-Document Summarization Model
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    Abstract:

    This paper introduces two models to describe dynamic evolution of network information: identify and analysis the document collection on the same topic in different stages. In order to construct dynamic of evolution content differences, two dynamic multi-document summarization models are presented, which are matrix subspace analysis model, text similarity cumulative model. Based on these models, some efficient dynamic sentence weighting algorithms are implemented. Experiments on the test data of Update Summarization in TAC 2008 and comparative results between new models and TAC 2008 evaluation, shows the effectiveness of the models.

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刘美玲,郑德权,赵铁军,于洋.动态多文档文摘模型.软件学报,2012,23(2):289-298

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History
  • Received:October 14,2010
  • Revised:December 09,2010
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  • Online: February 07,2012
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