Effect of Semantic Differences in Word Net-Based Similarity Measures

Assessing the semantic similarity\ of words is a generic problem in many research fields such as artificial intelligence, biomedicine linguistics, cognitive science Mid psychology The difficulty of this task lies in how to find an effective way to simulate the process of human judgement of word similarity in this paper we introduce the idea of semantic differences and commonalities between words to the similarity computation process Five new semantic similarity metrics are obtained after applying this scheme to traditional WordNet-based measures in an experimental evaluation of out approach on a standard 28 word pans dataset three of the measures outperformed their classical version, while the other two performed as well as their unmodified comae! parts