摘要
针对用户浏览网页的兴趣会随时间而变化这一现象,设计了一种网络用户兴趣迁移模式的挖掘模型。把用户的访问兴趣通过隐马尔可夫模型抽象成一种时间序列,以此反映用户兴趣的序列性,进而利用GSP算法从用户兴趣序列中挖掘出用户兴趣的迁移模式。实验证明该方法是有效的,从时间属性上更深层次地描述了用户兴趣的变化情况。
Focused on the phenomenon that the visited interest of user would change with time,a model of mining user＇s interest drift pattern was proposed.Abstracted the visited interest of user into a time sequence with the method of hidden Markov,which was used to reflect the sequential features of the user interest.Used GSP algorithm to mine the drift of user＇s visited interest pattern from the interested sequence of user.At last,verified the feasibility of the given model using the simulation experiments,and the model could give a deeper description of the draft of the visited interest on the attribute of time.
出处
《计算机科学》
CSCD
北大核心
2011年第5期175-177,219,共4页
Computer Science
基金
陕西省自然科学基金资助项目(SJ08-ZT15)
陕西省教育厅专项科研计划项目(08JK425)资助
关键词
兴趣迁移模式
隐马尔可夫模型
序列模式挖掘
User interest drift pattern
Hidden markov model
Sequential pattern mining
