Research on Method of Extracting Chinese Domain Terms Based on Rough and Fuzzy Clustering

Automatic extraction of domain terms is the basis of domain ontology learning. General linguistic resources such as WordNet and HowNet can be applied to extract only partial domain terms from domain unstructured texts. In this paper, we firstly extract partial terms by calculating domain relatedness between words by HowNet. Then the extracted terms are semantically clustered with fuzzy c-means clustering algorithm based on properties of rough sets. Finally more domain terms are extracted from unknown words according to the clustering results with the method of machine learning. The experimental results showed that the method can not only extract domain terms as more as possible, but also ensure higher precision.