基于兴趣文档集合游历便利性的站点结构优化模型

基于特定信息需求的网站用户游历其兴趣文档集合的便利性,建立了一种站点结构优化的数学模型,通过页组支持度与页组拓扑平均距离量化评估与挖掘站点中访问效率较低的内容文档集合为结构优化的兴趣页组,据此提出能综合评价站点访问效率的指标--WEB拓扑兴趣度,并通过分析新增超链接的影响因素设计了相应的站点结构优化方法,优化算法中采用遗传算法寻找最优组合的新增超链接组.实验结果表明:优化后的站点结构能有效改善信息搜索与获取行为的效率低下问题.

Website Structure Optimization Model Based on Convenience of User Navigating Through Its Interesting Web Page Group

An optimization model of website hyperlink structure based on the convenience of user navigating through its interesting web page group was proposed.First,web page group with low access efficiency was discovered by its support and its topology average distance;then a measure degree,website topology interest,which could overall indicate the website access efficiency was proposed;finally,the corresponding website structure optimization method was proposed,and genetic algorithm was used to find the best new added hyperlink group.Experiment results show that after optimization,the new website structure can effectively improve the problem of low efficiency of information foraging behavior.