Using WordNet to determine semantic similarity of words

Word and concept similarity assessment is one of the most important elements in natural language processing and information and knowledge retrieval. WordNet, as a popular concept hierarchy, is used in many such applications. Similarity of words in WordNet is also considered in recent researches. One of the new researches that uses WordNet, has calculated similarity between each two words by considering Depth of Subsumer of the words and Shortest Path between them. In this paper we have improved semantic similarity measure by modifying transfer functions of the previous research. We have tuned parameters of the transfer functions using particle swarm optimization. Based on our experimental results on a benchmark set by human similarity judgment, the resultant correlation has been improved.