Sense recognition research of hyponymy based on concept space

For the polysemy of hyponymy in the phase of building taxonomic hierarchy, this paper presents a method of sense recognition of hyponymy based on concept space. The problem of sense recognition of single concept is transformed into recognition of hyponymy in concept space. Firstly, the contexts of hyponymy are acquired iteratively using coordinate relation patterns. Secondly CiLin and the weight of feature words are used to construct a hyponymy-word vector space. Then LSA is used to reduce the dimension of the vector space. In the final phase, the senses of hyponymy can be recognized using average-group clustering. The relation of decreasing degree of similarity and threshold of clustering, and the effect of CiLin and LSA in experiment are analyzed. Experimental results show that the method is adequate of partitioning the senses the hyponymy.