A New Model of Information Content Based on Concept's Topology for Measuring Semantic Similarity in WordNet

Information content plays an important role in measuring semantic similarity of concepts. The conventional way of IC obtained is through statistical analysis of corpora. Recently corpora-independent model has attracted great concern in this area. This paper analyzes the state-of-art IC models, highlights important related issues, and presents a novel IC model based on concepts' topology in WordNet. Different from previous work, for a given concept, the depth itself, the number of its hyponyms, and the depth of every hyponym have been taken into considered. Experiment demonstrates that our approach is able to provide more accurate similarity evaluation and achieves significant performance than related works.