期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2012
卷号：5
期号：3
出版社：SERSC
摘要：Semantic similarity between word senses is hot topic in many applications of computational linguistics and artificial intelligence, such as word sense disambiguation, information extraction, semantic annotation and ontology learning. Many methods for calculating word sense similarity have been proposed. In recent years the methods based on WordNet have shown its talents and attracted great concern. In the paper, we present a new method in WordNet for calculating word sense similarity, which is noun and is-a relation based. We evaluate our method on the data set of Rubenstein and Goodenough, which is traditional and widely used. The correlation with human judgment is o.8804 in proposed measure, which is more close to human judgments than related works. Experiments show that our new measure significantly outperformed than other existing computational methods.
关键词：semantic similarity; information content based; WordNet
