Abstract: A user preferred browsing paths algorithm is proposed，and also be meaningful improved.The algorithm after improve：Firstly，two URL-URL matrixes are set up from Web logs according to Web site’s browsing paths，where referrer URL as rows，navigating URL as columns.Respectively，using the average visit times（divided by the number of characters in the website） and the frequency of visits as matrix element.Then，preferred browsing sub-paths will be discovered from the computation of this matrix．Finally，all the sub-paths are combined to generate a set of user preferred browsing paths.

摘要： 引入一种挖掘用户兴趣路径的算法，并对其进行有意义的改进。算法的主要思想是：首先利用Web日志建立以引用网页URL为行、浏览网页URL为列的两个网站访问矩阵，分别采用访问次数和平均到网页中字符数的访问时间为元素值。然后，通过对矩阵进行路径兴趣度计算得到兴趣子路径，最后进行合并生成用户兴趣路径集。