文献类型： 外文期刊
第一作者： Wei, Xuyang
作者： Wei, Xuyang;Li, Zhongliang;Zou, Tengfei;Yang, Guocai;Wang, Yan;Wang, Yan
作者机构：
关键词： Ant colony optimization;Users' navigation patterns;Interest;Web logs mining
期刊名称：INTELLIGENT AUTOMATION AND SOFT COMPUTING （ 影响因子：2.0； 五年影响因子：1.6 ）
ISSN： 1079-8587
年卷期： 2015 年 21 卷 3 期
页码：
收录情况： SCI
摘要： Web log mining is mainly to acquire users' interest navigation patterns from web logs and has been the subject of the web personalization research. In this paper, we define a new concept "interest pheromone" and present a group users' navigation paths model. Then we propose a simple algorithm based on improved Ant Colony Optimization (ACO) to mine users' dynamic interest. In this algorithm, three factors relative browsing time, access frequency and operation time are considered to measure the "interest pheromone", which better reflects users' real interest. Finally, we conduct the simulation experiments to contrast the accuracy of navigation patterns mined by our approach and existing approaches. Experimental results illustrate that the proposed paradigm can truly capture users' browsing preference effectively.
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