Collaborative content and user-based web ontology learning system

This paper presents a collaborative ontology learning approach for the implementation of an ontology-based Web content management system (OWCMS). The proposal system integrates two supervised learning approach - content-based learning and user-based learning approach. The content-based learning approach applies text mining methods to extract ontology concepts, and to build an ontology graph (OG) through the automatic learning of Web documents. The user-based learning approach applies features analysis methods to extract the subset of the ontology graphs, in order to build a personalized ontology by using intelligent agent approach to capture user reading habit and preference through their semantic navigation and search over the ontology-based Web content. This system combines the two methods to create collaborative ontology learning through an ontology matching and refinement process on the ontology created from content-based learning and user-based learning. The proposed method improves the validness of the classical ontology learning outcome by user-based learning refinement and validation.