关键词: 本体, 文档聚类, 概念, 消歧, 抽象度

Abstract: This paper suggests a novel text clustering scheme based on ontology,in order to overcome the shortcomings of traditional measures.The scheme firstly translates the feature terms of VSM into concepts by mapping and disambiguation with the aid of the ontology,Wordnet.Using the improved feature vector of VSM,the scheme can work in the semantic level.Subsequently,on the basis of twice feature selections,which can sharply decrease the complicacy of clustering,agglomerative clustering algorithm is applied.With the special semantic center vectors,scheme can adjust clustering by the abstract degree of concept for different requirements of users.In the experiment,the result shows the accuracy of this scheme is high,clusters can be explained by feature concepts,and adjustment is valid.

Key words: ontology, text clustering, concept, disambiguation, abstract degree