Web Site Structure and Content Recommendations
WI '04 Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence
A Knowledge Base for the maintenance of knowledge extracted from web data
Knowledge-Based Systems
A hybrid system for concept-based web usage mining
International Journal of Hybrid Intelligent Systems
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
Using SOFM to improve web site text content
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
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For many companies and/or institutions it is no longersufficient to have a web site and high quality products orservices. What in many cases makes the difference betweensuccess and failure of e-business is the potential of the respectiveweb site to attract and retain visitors. This potentialis determined by a site's content, its design, and technicalaspects, such as e.g. time to load the pages among others.In this paper, we concentrate on the content representedby free text of each of the web pages. We propose a methodto determine the set of the most important words in a website from the visitor's point of view. This is done combiningusage information with web page content arriving at a setof keywords determined implicitly by the site's visitors.Applying self-organizing neural networks to the respectiveusage and content data we can identify clusters of typicalvisitors and the most important pages and words foreach cluster. We applied our method to a bank's web site inorder to show its benefits.Institutions that perform consequently and regularly theproposed analysis can design their web sites according totheir visitors' needs and requirements and this way stayahead of their competitors.