摘要
用户在访问Web站点时会碰到很多问题,主要原因是Web站点对用户需求缺乏适应性。为了提高Web用户的服务质量和用户的满意度,在用户访问网站点击流形成频繁序列模式的基础上,提出基于距离函数的聚类分析以及基于时间相似度函数的二次聚类分析算法。该算法可以求取频繁序列的相关性和反映用户对网页的兴趣的相似度,对下一步改善Web站点的结构及存在形式使站点达到更好的效果起先导作用。
Difficulties in navigation through the Web are very often encountered by users, the main reason is the lack of adaptation of a Web site to its visitors＇needs. For the sake of promoting Web user＇s service quality and satisfactory, base on the frequency sequence pattern by the Web click flow frequency constitutes and adopt the analysis of the clustering algorithm according to the distance function and the time similarity function. The arithmetic which obtain the relativity of sequence and the similarity of user＇ s interest on a webpage can give us advice how to improve the Web site＇s structure and ontology.
出处
《计算机技术与发展》
2007年第9期18-20,共3页
Computer Technology and Development
关键词
频繁模式
相似度
聚类
数据挖掘
frequent pattern
similarity
clustering
data mining
