基于Web挖掘的路径划分模糊聚类算法的研究
Study on Path Segmentation Fuzzy Clustering Based On Web Mining
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摘要: 采用路径划分聚类算法, 对Web用户访问路径进行划分, 然后根据其相似度进行聚类, 依据分类系数和平均模糊熵来判定簇个数的最优解, 得到较好的聚类效果, 为最终挖掘出用户的访问模式奠定了良好的基础. 实验发现簇中心偏移次数明显减少, 中心长度有所提高, 证明算法具有较好的效率.Abstract: The clustering algorithm of path segmentation was used to separate web users access and cluster according to their similarity. fuzzy factor and average entropy clustering were used to determine the optimal solution, and clustering effect was better, and set a good foundation for the final excavation to the user’s access patterns. The results indicated that the efficiency of algorithm was better.