Semi-automatic Ontology Construction Based on Text Learning

摘要

This paper proposes a method of semi-automatic ontology construction based on text learning. Firstly, construct a core ontology by ontology tool, then extract domain related terms by both text classification method and keyword extraction method to produce ontology conception candidate set. Lastly, judge the semantic relationships between domain terms and ontology concepts by phrase similarity method, and add the matching concepts to the core ontology to finish the ontology expansion automatically. Experiment result shows that this method is feasible, which not only improves the construction efficiency, but also ensures the ontology quality.