摘要
有效的用户识别与用户细分是网站用户行为分析的基础.针对现有用户识别算法将注册用户和匿名用户均按匿名用户处理,导致用户分类不细致的问题,提出了一种匿名用户识别算法.该算法通过识别用户访问行为状态,采取页面访问路径和浏览时长匹配方式,进一步识别IP地址变化后混入纯匿名用户中的注册匿名用户,从而把用户细分为注册用户、假匿名用户和纯匿名用户.实验结果表明,该算法能够提高匿名用户识别率,更加准确地识别假匿名用户.
Valid user identification and user segment are the basis of user behavior analysis.For the user classification is oversimplified which leads by confusing anonymous users and registered users all as anonymous user in existing user identification algorithms,an anonymous user identification algorithm has been proposed.By identifying users＇ access behavior state and matching users＇ access path and browsing time length,the algorithm identifies the registered anonymous user mixed in the pure anonymous user due to the IP address change to classify user into registered login user,registered anonymous user,pure anonymous users.The experimental results indicate that the proposed algorithm can improve anonymous user identification rate,and identify the registered anonymous user much more accurately.
出处
《西南师范大学学报（自然科学版）》
CAS
北大核心
2015年第9期78-84,共7页
Journal of Southwest China Normal University(Natural Science Edition)
基金
重庆市自然科学基金项目(CSTC2012jjA40027)
"核高基"重大专项(2009ZX01038-002-002-2)
关键词
数据挖掘
匿名用户
用户识别
浏览路径
访问时长
data mining
anonymous user
user identification
access path
browsing time
