摘要
提出一种基于网页分类和网页加权的网民聚类算法，其基本思想是：先以各个网民对每个网页的点击量为依据，通过模糊等价矩阵聚类法对网页进行分类，并根据网页内容与深度确定网页的加权，即给每个网页一个分数，最后根据这个加权分数再次对网民进行聚类，即使用两次模糊等价矩阵聚类．
A clustering algorithm of net users based on web page classification and web page weight is proposed. The basic idea is as follows： firstly, web pages are classified by using the method of fuzzy equivalent matrix on the basis of hits amounts of each web page. Then, web page weight is set with its content and depth, that is, this method gives each web page a weighted score. At last, the net users are clustered according to this weighted scores, in fact, this method uses fuzzy equivalent matrix to cluster for two times.
出处
《北华大学学报（自然科学版）》
CAS
2008年第3期284-288,共5页
Journal of Beihua University（Natural Science）
基金
吉林省科技型中小企业创新基金(SC0601020)
关键词
网页分类
网页加权
模糊等价矩阵聚类
Web page classification
Web page weight
Fuzzy equivalent matrix cluster
