A stack-based Markov model in web page navigability measure

Cheng-Tzu Wang, Chih-Chung Lo, An-Pang Chang, Sheng-Kai Pan
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引用次数: 3

Abstract

Usability is critical to the success of a website and good navigability enhances the usability. Hence the navigability is the most important issue in designing websites. Many navigability measures have been proposed with different aspects. Applying information theory, a stack-based Markov model is proposed to represent the structure of a website and to include more surfing behavior. The dynamic users' log data is used to evaluate navigability of a web page. The entropy ratio is proposed to represent the navigability of web pages. Experimental results show the relation between entropy ratio and characteristic of a web page is quit close. Applying the entropy ratio of a web page, the web page can be recognized as a type of page which is good or not.
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基于堆栈的马尔可夫模型在网页可导航性度量中的应用
可用性对网站的成功至关重要,良好的可导航性可以增强可用性。因此,可导航性是网站设计中最重要的问题。人们从不同方面提出了许多通航措施。应用信息论,提出了一个基于堆栈的马尔可夫模型来表示网站的结构,并包含更多的浏览行为。动态用户日志数据用于评估网页的可导航性。提出用熵比来表示网页的可导航性。实验结果表明,熵比与网页特征之间的关系非常密切。利用网页的熵比,可以将网页识别为网页的好坏类型。
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