Ontology is applied to various fields of computer as a conceptual modeling tool, and is used to organize information and manage knowledge. On- tology extension is used to add the new concepts and relationship into the exist- ing 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 related- ness between words to find the potential concepts from text, denoted as the ex- tended concepts. And we take advantage of extension rules and subsumption analysis to find the relationship between concepts, which is used to add the ex- tended 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 reason- able and promising. It has a stronger competitiveness and application ability.
['Wei He', 'Shuang Li', 'Xiaoping Yang']
A Hybrid Approach for Extending Ontology from Text