摘要
电子商务混合入侵行为会造成企业经济受到损失,于是为了减少损失需要对其信息进行检索,从而及时有效的检索出入侵信息。文章提出了一种基于最大熵原理的入侵行为信息智能化检索方法,其中使用了两种离散方式将特征转化为离散数值,从而可以除去冗余干扰特征;再使用了3种特征选择方式,除去了噪声干扰特征。最后通过仿真实验得到文章所研究的检索方法具有效率快、精确度高的特点。
The mixed intrusion of e-commerce will cause losses to the enterprise economy,so in order to reduce losses,it is necessary to retrieve its information,so as to retrieve the intrusion information in a timely and effective manner.This paper proposes an intelligent retrieval method for intrusion behavior information based on the principle of maximum entropy.Two discrete methods are used to convert features into discrete values,so that redundant interference features can be removed;Three more feature selection methods are used to remove noise interference features.Finally,through simulation experiments,the retrieval method studied in this paper has the characteristics of fast efficiency and high accuracy.
作者
段立峰
DUAN Li-feng(Shaanxi Polytechnic Institute,Xianyang Shaanxi 712000,China)
出处
《粘接》
CAS
2020年第10期141-144,156,共5页
Adhesion
关键词
最大熵原理
电子商务
混合入侵
检索
principle of maximum entropy
e-commerce
mixed intrusion
retrieval
