用页组拓扑平均距离改善页面聚类算法

Enhanced Algorithm for Page Clustering by Using Topology Average Distance of Web Pages Group

提出一种支持站点结构优化的页面聚类改进算法,通过引入图论中的拓扑平均距离,量化评估与挖掘站点结构中访问效率较低的内容文档集合为结构优化的兴趣页组,挖掘的页组具有更高的兴趣性,并将兴趣页组挖掘算法融入到拓扑优化算法中。实验结果表明改进算法能更好地优化站点结构,较一般算法收敛性好。

An enhanced algorithm which supports Website structure optimization was proposed for page clustering. A quantitative criteria was proposed by introducing the average distance in graph and the low access efficiency Web content pages group was discovered as interesting page group for Website structure optimization. Thus, the enhanced algorithm can find out more interesting page groups than the normal algorithm. Meanwhile the mining algorithm was integrated into the topology optimization algorithm. Experiment results show that the enhanced algorithm can improve Website structure better and it converges more rapidly.