计算机技术与发展2012，Vol.22Issue(7)：95-98,4.
一种基于特征属性的Web用户模糊聚类改进算法
An Improved Web Users Fuzzy Clustering Algorithm Based on Features Property
摘要
Abstract
In this paper,present an improved Web men fuzzy clustering algorithm based on features property to reduce the computational complexity of conventional fuzzy c-means dusering algorithm and improve the effect of Web users clusering. Fust,establish Web user's interest degree matrix through the times and time of user's visited pages,mapping the Web user's interest degree matrix into die user's fea-tures property preference matrix according to the features property of item to reduce the data sparseness effectively. Based on the feature* property preference matrix, improved the conventional fuzzy c-means clusering algorithm. The proposed method first classifies duster centers into active and stable groups,then skips the distance calculations for stable clusters in toe iterative process to reduce the computational complexity of conventional fuzzy c-means clustering algorithm. Finally,die simulation demonstrates the feasibility and validity of the proposed method.关键词
特征属性/Web用户/模糊聚类/模糊C均值算法Key words
features property/Web users/fuzzy clustering/FCM分类
信息技术与安全科学引用本文复制引用
应玉龙..一种基于特征属性的Web用户模糊聚类改进算法[J].计算机技术与发展,2012,22(7):95-98,4.基金项目
宁波市自然科学基金(2010A610118) （2010A610118）
宁波市先进纺织技术与服装CAD重点实验室(2011ZDSYS-A-004) （2011ZDSYS-A-004）
