Web Usability : A Fuzzy Approach to the Navigation Structure Enhancement in a Website System, Case of Iranian Civil Aviation Organization Website

With the proliferation of World Wide Web, development of web-based technologies and the growth in web content, the structure of a website becomes more complex and web navigation becomes a critical issue to both web designers and users. In this paper we define the content and web pages as two important and influential factors in website navigation and paraphrase the enhancement in the website navigation as making some useful changes in the link structure of the website based on the aforementioned factors. Then we suggest a new method for proposing the changes using fuzzy approach to optimize the website architecture. Applying the proposed method to a real case of Iranian Civil Aviation Organization (CAO) website, we discuss the results of the novel approach at the final section.

Authors:

• Hamed Qahri Saremi
• Gholam Ali Montazer

Keywords:

• Web content
• Web navigation
• Website system
• Webusage mining.

References:

[1] Kim, W., Y.U. Song, and J.S. Hong, Web enabled expert systems using
hyperlink-based inference. Expert Systems with Applications, 2004: pp.
1-13.
[2] E.Rosen, D. and E. Purinton, Website design: Viewing the web as a
cognitive landscape. Journal of Business Research, 2004(57): pp. 787-
794.
[3] Lee, J.-H. and W.-K. Shiu, An adaptive website system to improve
efficiency with web mining techniques. Advanced Engineering
Informatics, 2004. 18: pp. 129-142.
[4] Benbunan-Fich, R., Using protocol analysis to evaluate the usability of a
commercial web site. Information & Management, 2001(39): pp. 151-
163.
[5] Spiliopoulou, M. and L.C. Faulstich. WUM: a web utilization miner. in
Workshop on the Web and Data Bases (WebDB(98)). March 1998.
Valencia, Spain. pp. 109-115.
[6] Nakayama, T., H. Kato, and Y. Yamane. Discovering the gap between
web site designers' expectations and users' behavior. in The 9th Int'l
World Wide Web Conference on Computer Networks. May 2000.
Amsterdam, Holland. pp. 811-822.
[7] Perkowitz, M. and O. Etzioni. Adaptive web sites: automatically
synthesizing web pages. in The 15th National Conf. on Artificial
Intelligence. 1998. pp. 727-732.
[8] Perkowitz, M. and O. Etzioni. Towards adaptive sites: conceptual
framework and case study. in The 8th Int'l World Wide Web
Conference. May 1999. Toronto, Canada.
[9] Vrazalic, L. Website usability in context: an activity theory based
usability testing method. in The national conference on Transformational
Tools for 21st Century Minds. 2003. pp. 41-47.
[10] Blackmon, M.H., M. Kitajima, and P.G. Polson. Repairing usability
problems identified by the cognitive walkthrough for the web. in
SIGCHI conference on Human factors in computing systems. 2003.
Florida, USA. pp. 497-504.
[11] Huang, M.-H., Web performance scale, Information & Management,
2004. Article in Press.
[12] Wang, Q., D.J. Makaroff, and E.H. keith. Characterizing customer
groups for an e-commerce website. in The 5th ACM conference on
Electronic commerce. 2004. USA. pp. 218-227.
[13] Srivastava, J., et al., Web usage mining: discovery and applications
usage patterns from web data. SIGKDD Explorations, 2000. 1(2): pp.
12-23.
[14] Zhou, B., et al. Website link structure evaluation and improvement based
on user visiting patterns. in The 12th ACM conference on Hypertext and
Hypermedia. 2001. Denmark. pp. 241-244.
[15] Pal, S.K., V. Talwar, and P. Mitra, Web mining in soft computing
framework: relevance, state of the art and future directions. IEEE
Transaction on Neural Networks, 2002. 13(5): pp. 1163-1177.
[16] Mitra, S., S.K. Pal, and P. Mitra, Data mining in soft computing
framework: a Survey. IEEE Transaction on Neural Networks, 2002.
13(1): pp. 3-14.
[17] Mitra, S. and H.L. Larsen, Special issue on web mining using soft
computing. Fuzzy Sets and Systems, 2004. 148: pp. 1-3.
[18] Arotaritei, D. and S. Mitra, Web mining: a survey in the fuzzy
framework. Fuzzy Sets and Systems, 2004. 148: pp. 5-19.
[19] Saudi, A. and M.H.A. Hijazi. Using similarity measures and association
rule for web personalization. in M2USIC. October 2004. Malaysia. pp.
16-19.
[20] Kim, K.-J. and S.-B. Cho, Personalized mining of web documents using
link structures and fuzzy concept networks. Applied Soft Computing,
2005. Article in Press.
[21] Gorzalczany, M.B., Computational intelligence systems and
applications: neuro-fuzzy and fuzzy neural synergisms. 2002: Springer.
364.