A simplified edge-counting method for measuring semantic similarity of concepts

Semantic similarity measuring between concepts is the basis for many applications. To get an easy way to compute semantic similarity, we proposed a simplified approach combining two information sources: the shortest path length and depth of the least common subsumber (LCS) of compared concepts, to calculate the semantic similarity between concept pairs. The experimental results suggest that the approach obtains a relatively high correlation value compared with the related work, and there exist a nonlinear relationship between semantic similarity and the shortest path length of the compared concept pairs. In addition, the method relies on the most commonly available information sources, which makes it more feasible. The proposed method can be applied to the field of information management and knowledge engineering.