Title :
A stack-based Markov model in web page navigability measure
Author :
Wang, Cheng-tzu ; Lo, Chih-chung ; Chang, An-pang ; Pan, Sheng-kai
Author_Institution :
Dept. of Comput. Sci., Nat. Taipei Univ. of Educ., Taipei, Taiwan
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.
Keywords :
Markov processes; Web sites; information theory; Web page navigability measure; Web site; dynamic user log data; entropy ratio; information theory; stack-based Markov model; Abstracts; Business; Markov processes; Silicon; Web pages; information theory; stack-based;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2012 International Conference on
Conference_Location :
Xian
Print_ISBN :
978-1-4673-1484-8
DOI :
10.1109/ICMLC.2012.6359639