Measure Semantic Distance in WordNet Based on Directed Graph Search

Many researchers make use of WordNet to measure semantic distance, but rarely describe and, further more, analyze an algorithm which is in specialty to find paths, called semantic relations in this paper, between two concepts in WordNet. Searching in all semantic relations is an important step in measuring semantic similarity. In this paper, we propose two algorithms, HS (hierarchy spread) and BDOS (bidirection one step), to search the relation with shortest semantic distance in WordNet. HS takes Hyponym and Hypernym into consideration at first, while BDOS searches semantic relations from two start concepts and dealing with all four relations at the same time. Moreover, dynamic threshold is brought in BDOS to control path expansion iteration. After experiments, we make astatistic analysis and comparison between these two algorithms and another approach which is proposed earlier for measuring semantic similarity by researcher named Yang. The experiments show that BDOS gives a better performance and accuracy.