基于增量式蚁群聚类的用户访问模式挖掘  

Mining user navigation pattern using incremental ant colony clustering

作　　者：沈洁[1] 林颖[1] 陈志敏[1] 赵敏涯[1] 

机构地区：[1]扬州大学计算机科学与工程系,江苏扬州225009

出　　处：《计算机应用》2005年第7期1654-1657,1660,共5页journal of Computer Applications

基　　金：江苏省高校自然科学基金项目(02KJB520013)

摘　　要：提出一种新的用户访问模式增量式聚类算法:首先引入一种新的用户兴趣表示方法构造用户访问特征对象,再基于蚁群聚类的基本思想,利用人工蚂蚁依相邻区域对象相似性拾起或放下对象实现聚类;然后使用一种类解体机制,随着用户兴趣度的变化而形成新的类别,从而实现增量式聚类更新发现用户新的访问兴趣。实验结果表明,该方法能动态有效地实现增量式聚类。A novel algorithm for mining user navigation pattern with incremental clustering was presented. Firstly, a new method for expressing user interest was introduced to construct user profile object. Based on the basic concept of ant colony clustering, artificial ants were used to pick up or drop down object to implement clustering by analyzing the similarity with other local regional objects and. Then a mechanism of decomposing clusters was used to form new clusters when users' interests changed. Experimental results show that the method can adaptively and efficiently achieve incremental clustering.

关 键 词：蚁群聚类 用户访问模式 增量式聚类 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]