网络敏感信息动态特征的抽取方法

网络的匿名性、开放性、平等性、交互性等特点不可避免地会出现一些不和谐“杂音”,人们怎样才能吸取精华、去其糟粕,已经成为网络信息安全迫切需要解决的问题.针对传统的文本特征抽取方法,在应用于敏感信息过滤时出现的时间滞后、准确性低、自适应性差等问题,以网络舆论观点文本为研究对象,结合敏感信息特性,提出融合意见挖据和自然语言处理技术的敏感信息动态特征抽取方法,实验表明,本方法对敏感信息过滤有明显优势,实现了字典的动态维护.

Research on Algorithm of Network Sensitive Information Features Extracting

Because of the characteristics of anonymity,openness,equality and interaction in internet,it is inevitab there will be some disharmonious ‘noise’,and how to absorb the essence and discard the dregs,has become an urgent need to solve the problem in the network information security.Aiming at the problems of time lag,low accuracy and poor adaptability in applied traditional text feature extraction method to sensitive information filtering,this paper put network public opinion as the research object,taking into consideration the characteristics of sensitive information.A method of sensitive information dynamic feature extraction is put forward for fusion opinions mining and natural language processing technology.The experimental results show that the method has obvious advantages to the sensitive information filtering and the dynamic maintenance of the dictionary is realized.