A Knowledge Base for the maintenance of knowledge extracted from web data

Abstract

By applying web mining tools, significant patterns about the visitor behavior can be extracted from data originated in web sites. Supported by a domain expert, the patterns are validated or rejected and rules about how to use the patterns are created. This results in discovering new knowledge about the visitor behavior to the web site. But, due to frequent changes in the visitor's interests, as well as in the web site itself, the discovered knowledge may become obsolete in a short period of time. In this paper, we introduce a Knowledge Base (KB), which consists of a database-type repository for maintaining the patterns, and rules, as an independent program that consults the pattern repository. Using the proposed architecture, an artificial system or a human user can consult the KB in order to improve the relation between the web site and its visitors. The proposed structure was tested using data from a Chilean virtual bank, which proved the effectiveness of our approach. (c) 2006 Elsevier B.V. All rights reserved.