基于频繁链表-存取树的Web用户浏览模式挖掘算法

摘要

To observe Web user’s browsing behaviors which help analysis user’s preferred browsing patterns set and personal interests, this paper apply the structure of frequent linked list combined with access tree, build and update the structure with captured web users browsing tracks, mining for user’s preferred browsing patterns with the idea of merging. By comparing the updating and mining conditions of this algorithm and GSP algorithm on the same test set, experiment show significantly advantage of this algorithm in accuracy and efficiency. Meanwhile, the algorithm also provides a theoretical basis for the subsequent long-term observational study.%为了观察网络用户浏览行为以研究用户偏爱的浏览模式集和个人兴趣，本文采用频繁链表结合存取树的增量式结构，使用捕获的网络用户浏览轨迹构建、更新该结构并使用同类合并的思想挖掘该结构以获得用户偏爱浏览模式集。实验通过对比本算法与GSP算法在同一测试集上的更新和挖掘情况，证明本算法在准确度和效率上都大幅领先。同时，该算法也为后续的长期观察研究提供了理论基础。