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Research on Filtration System of Network Negative Information on the Basis of Naive Bayes

机译:基于Naive Bayes的网络负面信息过滤系统研究

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The difficulty of filtrating network negative information lies in how to classify information correctly. As one of the classification method with the advantage of strong robustness and good understandability in the field of pattern classification, Naive Bayes has been used widely. A method for filtrating network negative information on the basis of Naive Bayes, improvement proposals aiming at the disadvantages of Naive Bayes and amelioration of erroneous judgment of negative information by setting threshold value k have been put forward in this article. The experiment shows that by adjusting threshold value k can the integrity of the system can be optimum and can favorable application effects be achieved.
机译:过滤网络否定信息的难度在于如何正确对信息进行分类。作为具有强大鲁棒性优势的分类方法之一,在图案分类领域的领域,朴素的贝叶斯被广泛使用。在本文中提出了一种在朴素贝叶斯的基础上过滤网络负面信息的方法,提出了一种通过设定阈值k的难度贝叶斯的缺点以及通过设定阈值k的否定信息的拒绝判断的缺点。实验表明,通过调整阈值k可以是系统的完整性,可以实现最佳的应用效果。

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