摘要
互联网技术的发展日新月异,Web数据是海量的,同时网络用户的浏览兴趣也是不断变换的。为了满足用户兴趣不断变换的需求,更好地实现个性化推荐,提出了一种新的Web用户会话实时聚类算法。算法分析验证了该算法可以提高聚类速度,能更好地满足用户的需求。
As the development of the internett,he number of the web data is becoming more large,and the interests of the web users are various.In order to satisfy the needs of the users whose interests are changeable,and realize personalized rec-ommendationt,his paper gives a new realtime clustering algorithm about web user session.The experiment results show that this algorithm can improve the clustering speed,and can satisfy the needs of the users.
出处
《计算机工程与应用》
CSCD
北大核心
2010年第35期142-144,共3页
Computer Engineering and Applications
基金
国家自然科学基金(No.60674056)
辽宁省高校优秀青年骨干教师基金~~
关键词
Web数据
个性化推荐
用户会话
实时聚类
Web data
personalized recommendation
user sessionr
ealtime clustering
