基于支持向量机与朴素贝叶斯的犯罪度理论研究

Research on Crime Degree Theory of Internet Speech Based on Support Vector Machine and Naive Bayes

为使安防系统具有犯罪预警的功能,以达到真正意义的智能化,提出网络言论犯罪度概念。该概念指某个体通过社交网络言论表现出的犯罪可能性。通过对犯罪心理与言论特征之间关系的研究,提出了一种基于朴素贝叶斯与SVM(Support Vector Machine)的网络言论犯罪度理论。该理论运用朴素贝叶斯和SVM等机器学习方法,结合犯罪心理学,建立了网络言论犯罪度理论框架与数学模型。实验表明,基于该理论的预警系统具有较好的犯罪预警能力。

In order to make the security system has the capability of early warning of crime,to achieve the real meaning of intelligent. Crime degree theory of internet speech is put forward,it refers to an individual＇s possibility of crime,which is shown by social network speech. The theory used multiple analytical methods such as naive bayes and SVM（Support Vector Machine）,combining criminal psychology,establishing the theoretical framework and mathematical model. Experimental result has shown that it works well.