A hybrid system for concept-based web usage mining
International Journal of Hybrid Intelligent Systems
Semantic Web Usage Mining by a Concept-Based Approach for Off-line Web Site Enhancements
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Adaptive Web SitesA Knowledge Extraction from Web Data Approach
Proceedings of the 2008 conference on Adaptive Web Sites: A Knowledge Extraction from Web Data Approach
Web site improvements based on representative pages identification
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Conceptual classification to improve a web site content
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
| Hi-index | 0.00 |
The internet has become a big battle field where organizations are trying to keep their present clients and to gain new ones. Two important weapons that the organizations have are to make a good web site design and to have a content interesting for the visitors. To improve the web site content many tools have been developed. However, it is hard to figure out how to apply these changes. Furthermore, in complex web sites, this is a non trivial task. We propose a novel approach that helps to improve a web site content using a SOFM and performing a reverse clustering analysis that allows us to gather the most representative web pages from a web site, using this small set of pages as a guideline of how these enhancements should be performed. The effectiveness of the method was tested in a real web site.