基于Web文本挖掘算法预防现实危害的研究

基于Web文本挖掘算法预防现实危害的研究
吴威
【期刊名称】《信息网络安全》
【年(卷),期】2016(000)009
【摘要】随着互联网的快速普及，人们已经习惯利用互联网进行交流。

由于互联网存在信息交流快速、社会反馈和社会规范缺乏等特性，人们交流也变得更加自由和极端，表达的情绪也更加真实。

这导致人们的注意力主要集中在信息本身，而忽略社会规则。

人们在网上发表的负面言论，往往是一种负面情绪的表达，这种情绪积累到一定程度时，很可能演变为现实危害。

文章主要介绍如何利用Web文本挖掘技术及基于朴素贝叶斯分类器的EM算法对Web文本数据进行情感分析，将情感分为正面、中性和负面，并且对负面信息进行归类、分析和预警，以预防现实危害的发生。

%As the rapid spread of the internet, people have gotten used to communicating with others through internet. However, because of the rapid exchange of information and the lack of social feedback and social norms, people become more free and extreme, and the expression of emotion is more real, which leads that people intend to focus on information itself and ignore the social regulations. Remarks written by net citizens are always negative because the emotions they try to express are negative. Moreover, the accumulation of negative emotions on internet will develop into social crisis in reality. This article primarily introduces the emotional analysis of Web textual data by using Web text mining technology and EM algorithm based on native Bayes classiifer, which
divides emotions on internet into positive emotions, neutral emotions and negative emotions. Meanwhile, the emotional analysis method is able to take precautions against social crisis in reality by the classiifcation, analysis and early warning of negative information.
【总页数】5页(P40-44)
【作者】吴威
【作者单位】内蒙古公安厅网安总队，内蒙古呼和浩特010050
【正文语种】中文
【中图分类】TP309
【相关文献】
1.基于Web链接结构的挖掘算法研究与应用 [J], 陈丽萍
2.基于Web传统网络的竞争对手挖掘算法的研究 [J], 李桂萍;
3.一种基于反向文本频率互信息的文本挖掘算法研究 [J], 周戈
4.语义文本挖掘算法优化研究 [J], 刘建君
5.基于LDA模型的大规模文本挖掘算法研究 [J], 董薇;庞峰;顾炜江
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