Instances driven adaptive ontology learning
Qiushuang Chen · Computer Engineering and Applications Journal · 2009
To solve problems in knowledge management,an adaptive ontology learning approach based on metadata of knowledge resources is proposed by integrating clustering algorithm and ODP (Open Directory Project).Ontology concepts are generated by clustering documents based on their metadata,and concept hierarchy is formed based on the hierarchy of mapped concepts in ODP.In order to track the changes in knowledge,adaptive ontology learning is conducted to update the ontology and enrich ontology concepts based on the changes of cohesion and correlation of clusters.The adaptive ontology learning approach proposed in this paper can reflect evolution process and tendency in research area,and meet demands for knowledge management of knowledge organization and knowledge sharing of researchers.Experimental result demonstrates the validity of the approach.