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    顾奕哲, 林家骏. 基于软信息的结构化转换[J]. 华东理工大学学报(自然科学版), 2014, (5): 631-638.
    引用本文: 顾奕哲, 林家骏. 基于软信息的结构化转换[J]. 华东理工大学学报(自然科学版), 2014, (5): 631-638.
    GU Yi-zhe, LIN Jia-jun. Structural Transformation Based on Soft Information[J]. Journal of East China University of Science and Technology, 2014, (5): 631-638.
    Citation: GU Yi-zhe, LIN Jia-jun. Structural Transformation Based on Soft Information[J]. Journal of East China University of Science and Technology, 2014, (5): 631-638.

    基于软信息的结构化转换

    Structural Transformation Based on Soft Information

    • 摘要: 随着文本信息(软信息)对多传感器信息融合的影响不断加深,如何形成一个有效的软信息结构化转换模型,给予计算机和传感器更多可融合的结构化软信息,成为了一个重要的任务。针对软信息结构化问题,即文本表示问题,首先对文本分类技术中向量空间模型的TF IDF权重进行研究;然后针对其结构化有效性方面的不足,通过引入事件全局权重和信息增益对TF IDF权重进行特征项关于文本主旨的信息及特征项在文本类间的分布信息补充、完善和实现软信息的结构化表示;最后通过实验验证了该改进方法对软信息结构化转换的可行性和有效性。

       

      Abstract: With the deeper and deeper influences of soft information on multiple sensor information fusion, an important problem is how to build an effective information structural transformation model and provide more fused structured soft information for computers and sensors. For the structural transformation of the soft information, i.e., text representation, this paper firstly studies the TF IDF weight based on the vector space model in the text classification technology. And then, aiming at the shortcoming of the structural transformation, both event global weight and information gain are introduced to supplement the text theme information and the item distribution information such that the structural description of soft information will be improved and implemented. Finally, the simulation results show the feasibility and effectiveness of structural transformation of soft information by the proposed method in this work.

       

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