A stack-based Markov model in web page navigability measure
Cheng‐Tzu Wang, Chih-Chung Lo, An-Pang Chang, Sheng-Kai Pan · 2012
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.