Word net based Method for Determining Semantic Sentence Similarity through various Word Senses

Semantic similarity is a confidence score that replicates semantic equivalence between the meanings of two sentences. Determining the similarity among sentences is one of the critical tasks which have a wide-ranging impact in recent NLP applications. This paper presents a method for identifying semantic sentence similarity among sentences using semantic relation of word senses across the different synsets using Wordnet for different part of speech of words. This method firstly detects all the semantic relations (hypernym, hyponym, holonym, meronymy etc.) considering the word as a noun and all the sense relations considering word as a verb from Wordnet respectively. Then it uses common senses between the two sets as Noun and Verb, for two input words for the calculation of semantic word similarity score. As sentence is made up of different words, these word similarity scores have been used for calculation of semantic sentence similarity among the sentences. It is difficult to achieve a high precision score because the exact semantic meanings will not be understood simply. However proposed method outperforms in comparison with existing methods. The evaluation is done for sentences using SemEval-12 Task 6 (TestGold-Set) with respect to human ratings.