基于数据挖掘的计算机用户行为分析与识别

Analysis and Recognition of Computer User Behavior Based on Data Mining

随着互联网技术的快速发展,网络已经成为人们生活及工作中不可或缺的一部分,本文通过对网络用户上网时所表现出来的行为进行分析研究,探索其行为特征及行为模式,建立计算机用户行为模型,利用聚类分析技术及相关算法建立了一个计算机用户行为分析识别系统,通过对网络用户日志数据所表现出来的行为进行预处理、模式挖掘及聚类分析实现了用户身份识别功能。并对系统的准确率和误差进行了分析,最后对该模型的完善和改进提出了若干设想。

With the rapid development of Internet technology,the network becomes an indispensable part of people's life and work.This paper analyses and studies the behavior of network users when they surf the Internet,explores their behavior characteristics and behavior patterns,establishes a computer user behavior model,and establishes a computer user behavior analysis knowledge by using clustering analysis technology and related algorithms.The user identification function is realized by pre-processing,pattern mining and clustering analysis of the behavior of the log data of network users.The accuracy and error of the system are tested and analyzed by statistics.Finally,some suggestions are put forward to improve the model.The realization of computer user behavior recognition system is of great significance to the development of network intelligent service and big data application.