Google Scholar

##plugins.themes.academic_pro.article.sidebar##

Published
Apr 12, 2015
Download
PDF
Statistic
Read Counter : 32 Download : 23

Downloads

Download data is not yet available.

##plugins.themes.academic_pro.article.main##

Abstract

To style effective information processing system user navigation may well be an enormous challenge. A main reason is that website|internet site|site|computer|computing machine|computing device|data processor|electronic computer|information processing system} developers have to be compelled to style a web site otherwise than the other users. completely different strategies have to be compelled to be generated to relink the WebPages, so the user navigation ar typically merely done. The new organized ways ar unpredictable, disorienting worth can’t be analyzed. This paper introduces information processing system whereas not substantial changes. User navigation may be reduced victimization mathematical programming and together alteration to Structure. The Result shows that it improved its user navigation and together it's effectively solved. to boot we've got an inclination to outlined 2 all completely different methods: assess performance of information processing system and real information set. The result together shows that user navigation has been improved greatly. The observation is disoriented user ar quite that of improved structure users.

Index Terms— net Personalization, net Transformation,DOM Tree, greatest Forward Reference, mini Sessions, Out- Degree Threshold, web site style, User Navigation, Web Mining, Mathematical Programming.

##plugins.themes.academic_pro.article.details##

Author Biographies

Pratik Kawale, Urvi Pimparkar, Pooja Singh, Sandip Institute of technology And Research Centre, Nashik, Maharashtra, 422213

BE IT

Amol Potgantwar, Sandip Institute of technology And Research Centre, Nashik, Maharashtra, 422213

HOD, IT Dept
How to Cite
Pooja Singh, P. K. U. P., & Potgantwar, A. (2015). Website Structure Improvement using User Navigation Monitoring and Web Mining. International Journal of Emerging Trends in Science and Technology, 2(04). Retrieved from http://igmpublication.org/ijetst.in/index.php/ijetst/article/view/617

References

1. Pingdom, Internet 2009 in Numbers, [Online] Available: http://royal.pingdom. com/2010/01/22/internet-2009-in-numbers/, 2010.
2. J. Grau,US Retail e-Commerce: Slower But Still Steady Growth, [Online] Available: http://www.emarketer.com/ Report. aspx?code=emarketer 2000492, 2008.
3. Internetretailer, Web Tech Spending Static-But High-for the Busiest E-Commerce Sites, [Online] Available: http://www. internetretailer. com/ dailyNews.asp?id = 23440, 2007.
4. D. Dhyani, W.K. Ng, S.S. Bhowmick,A Survey of Web Metrics, ACM Computing Surveys, Vol. 34, No. 4, pp. 469- 503, 2002.
5. X. Fang, C. Holsapple,An Empirical Study of Web Site Navigation Structures Impacts on Web Site Usability, Decision Support Systems, Vol. 43, No. 2, pp. 476-491, 2007.
6. J. Lazar,”Web Usability: A User-Centered Design Approach”, Addison Wesley, 2006.
7. D.F. Galletta, R. Henry, S. McCoy, P. Polak,When the Wait Isnt So Bad: The Interacting Effects of Website Delay, Familiarity, and Breadth, Information Systems Research, Vol. 17, No. 1, pp. 20-37, 2006.
8. J. Palmer,Web Site Usability, Design, and Performance Metrics, Information Systems Research, Vol. 13, No. 2, pp. 151-167, 2002.
9. V. McKinney, K. Yoon, F. Zahedi,The Measurement ofWeb- Customer Satisfaction: An Expectation and Discon-firmation Approach, Information Systems Research, Vol. 13, No. 3, pp. 296-315, 2002.
10. T. Nakayama, H. Kato, Y. Yamane, Discovering the Gap between Web Site Designers Expectations and Users Behavior, Computer Networks, Vol. 33, pp. 811-822, 2000
11. M. Perkowitz, O. Etzioni,Towards Adaptive Web Sites: Conceptual Framework and Case Study, Artificial Intelligence, Vol. 118, pp. 245-275, 2000.
12. J. Lazar,”User-Centered Web Develop-ment”, Jones and Bartlett Publishers, 2001.
13. Y. Yang, Y. Cao, Z. Nie, J. Zhou, J. Wen,Closing the Loop in Webpage Understanding, IEEE Trans. Knowledge and Data Eng., Vol. 22, No. 5, pp. 639-650, May 2010.
14. J. Hou, Y. Zhang,Effectively Finding Relevant Web Pages from Linkage Information, IEEE Trans. Knowledge and Data Eng., Vol. 15, No. 4, pp. 940-951, July/Aug. 2003.