Knowledge fusion model research based on granular computing theory
基于粒度计算理论的知识融合模型研究

In order to solve the problem of knowledge fusion and innovation from multiple distributed sources, this paper proposed controlled folksonomy. The result improved tagging precision of knowledge resources and reduced the cost of know-ledge organization. Furthermore, in order to eliminate the heterogeneity of ontology modules and construct the domain ontology with consistent semantic, it proposed quotient-let space methods. It applied granular computing theory in the field of knowledge integration. Quotient-let space method decomposed and reconstructed the distributed ontology modules to form domain ontology with simplicity and semantic consistency. Finally, it adopted an empirical analysis to verify the proposed method by Protégé. The conclusion shows that themethod is effective.