WebKIV: Visualizing Structure and Navigation forWeb Mining Applications
Full Text: webmining.pdf
A significant part of the web mining problem is simply in understanding the value of any mining method. For example, the value of web mining to improve user navigation is even more challenging if one can’t visualize the differences over a large collection of web pages or a significant structure within the existing web. We present WebKIV, a tool we’ve developed to help us visualize our own results in web mining. WebKIV combines strategies from several other web visualization tools, to provide a single method of visualizing web structure, and the results of web mining on that structure. We summarize the value of web visualization tools along the dimensions of scale (can one visualize small and large structures), navigation dynamics (can one visualize navigation dynamically or statically), and cumulative usage (can one distinguish individual and aggregate web usage). We then show how WebKIV provides a way of visualizing the results of web mining in a way that distinguishes properties along all three of these dimensions.
Citation
T. Zheng, Y. Niu, J. Chen, R. Goebel. "WebKIV: Visualizing Structure and Navigation forWeb Mining Applications". IEEE, pp 13-17, October 2003.| Keywords: | machine learning |
| Category: | In Conference |
BibTeX
@incollection{Zheng+al:IEEE03,
author = {Tong Zheng and Yonghe Niu and Jiyang Chen and Randy Goebel},
title = {WebKIV: Visualizing Structure and Navigation forWeb Mining
Applications},
Pages = {13-17},
booktitle = {},
year = 2003,
}Last Updated: June 04, 2007Submitted by Staurt H. Johnson
