Abstract
This chapter 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. Intelligent agent approach is employed 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 userbased learning refinement and validation.
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© 2011 Springer-Verlag Berlin Heidelberg
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Lim, E.H.Y., Liu, J.N.K., Lee, R.S.T. (2011). Collaborative Content and User-Based Web Ontology Learning System. In: Knowledge Seeker - Ontology Modelling for Information Search and Management. Intelligent Systems Reference Library, vol 8. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17916-7_12
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DOI: https://doi.org/10.1007/978-3-642-17916-7_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17915-0
Online ISBN: 978-3-642-17916-7
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