Web日志与浏览行为结合下的用户浏览兴趣数据挖掘分析  

Analysis of user′s browsing interest data mining combining Web log with user′s browsing behavior

作　　者：李珊[1] 刘继超[1] 邵芬红[1] 

机构地区：[1]燕京理工学院,河北三河065201

出　　处：《现代电子技术》2017年第5期22-25,共4页Modern Electronics Technique

基　　金：河北省科学技术厅课题(15210128):基于用户兴趣多维数据的Web挖掘可视化平台的设计与实现

摘　　要：针对用户浏览兴趣模式数据的收敛性和准确度不高的问题,提出一种基于Web日志与用户浏览行为结合的用户浏览兴趣模式数据挖掘模型。首先设计Web日志与用户浏览行为结合的用户浏览兴趣模式数据信息流模型,进行用户浏览兴趣模式的频繁项特征提取和Qo S预测;然后采用Web日志与用户浏览行为结合的行为调度模式自适应检索用户浏览网页的兴趣特征点,实现语义特征匹配,达到用户浏览兴趣模式数据挖掘的目的;最后通过仿真实验实现性能验证。结果表明,该方法的用户浏览兴趣特征点的匹配度高,数据挖掘精度得到提升,展示了优越性能。Since the data of the user＇s browsing interest patterns has poor convergence performance and low accuracy, a user＇s browsing interest patterns＇ data mining model based on the combination of the Web log and user＇s browsing behavior is proposed. The data information flow model of the user＇s browsing interest pattern based on the combination of the Web log with user＇s brow- sing behavior was designed to extract the frequent item feature of the user＇s browsing interest pattern and predict the QoS. The be- havior scheduling mode combining the Web log with user＇s browsing behavior is used to retrieve the interest feature points of the webpage browsed by the user adaptively to match the semantic feature, and mine the data of the user＇s browsing interest pattern. The performance of the model was verified with simulation experiment. The results show that the method can highly match the interest feature points of the webpage browsed by the user, improve the data mining accuracy, and show its superior performance.

关 键 词：WEB日志 用户浏览行为 兴趣模式 数据挖掘 

分 类 号：TN911.34[电子电信—通信与信息系统] TP391[电子电信—信息与通信工程]