An Area Concept Extraction Algorithm Based on Association Rule

Ontology learning is from a given area document sets automatic or semi-automatic extraction terms to construct a domain ontology. Area concept extraction is one of the most important aspects in building ontology. In this paper, we proposed an improved area concept extraction algorithm. In the algorithm, we firstly employed association rule algorithm to obtain the similarity between the sememes, and then used the similarity between the sememes to find the similarity between area concepts. Finally our paper achieves the whole area concepts extraction process. By analyzing the experimental results shows the effectiveness and correctness of the algorithm.