A Hybrid Approach for Extending Ontology from Text

Ontology is applied to various fields of computer as a conceptual modeling tool, and is used to organize information and manage knowledge. Ontology extension is used to add the new concepts and relationship into the existing ontology, which is a more complex task. In this paper, we propose a hybrid approach for ontology extension from text using semantic relatedness between words, which exploit co-occurrence analysis, word filter and semantic relatedness between words to find the potential concepts from text, denoted as the extended concepts. And we take advantage of extension rules and subsumption analysis to find the relationship between concepts, which is used to add the extended concepts into the existing ontology. The improved recall, precision and F1-Measure have been presented and used to evaluate our method proposed in this paper. Experimental results show that the proposed method is more reasonable and promising. It has a stronger competitiveness and application ability.