An Approach for Enhanced Web Site Composition via Well-Dressed Clustering
Abstract
Development of websites to facilitate effective user navigation is the
challenging task observed these days. Because the way web developers think and
design the system is quite different from that of the user. Different methods
have been projected to re-link WebPages in order to recover navigability using
user direction-finding data. The fully reorganized emerging structure can be
highly impulsive, and the cost of disorienting users after the changes remains
unanalyzed. The proposed system presents architecture to cluster the usage
statistics of all the users to re-link WebPages. The re-ordering or reforming
will mostly be based on clusters generated. Hence an optimal selection of
clusters is significant step in implementation of the system. Hence system uses
an enhanced K means clustering algorithm where in the number of clusters
(optimal) can be routinely designed and clusters are generated consequently.
The system also develops a arithmetical programming model to recover the user
navigation on a website. The system is imagined the deliver the functionality
of a test bench website for data collection and then reorder it based on
statistics collected to present the effectiveness of our model.
J. Palmer, “Web Site Usability,
Design, and Performance Metrics,” Information Systems Research, vol. 13, no. 2,
pp. 151-167, 2002.
T. Nakayama, H. Kato, and Y.
Yamane, “Discovering the Gap between Web Site Designers’ Expectations and
Users’ Behavior,” Computer Networks, vol. 33, pp. 811-822, 2000.
M. Perkowitz and O. Etzioni,
“Towards Adaptive Web Sites: Conceptual Framework and Case Study,” Artificial
Intelligence, vol. 118, pp. 245-275, 2000.
J. Hou and 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.
R. Gupta, A. Bagchi, and S. Sarkar,
“Improving Linkage of Web Pages,” INFORMS J. Computing, vol. 19, no. 1, pp.
127-136, 2007.
M. Eirinaki and M. Vazirgiannis,
“Web Mining for Web Personalization,” ACM Trans. Internet Technology, vol. 3,
no. 1, pp. 1-27, 2003.
C.C. Lin and L. Tseng, “Website
Reorganization Using an Ant Colony System,” Expert Systems with Applications,
vol. 37, no. 12, pp. 7598-7605, 2010.
Y. Fu, M.Y. Shih, M. Creado, and C.
Ju, “Reorganizing Web Sites Based on User Access Patterns,” Intelligent Systems
in Accounting, Finance and Management, vol. 11, no. 1, pp. 39-53, 2002.
“Facilitating Effective User
Navigation through Website Structure Improvement”, Min Chen and Young U. Ryu ,
Knowledge and Data Engineering, Vol. 25, No. 3, March 2013.
