An Approach for Finding Semantic Relatedness Score Between Two Sentences Based on their Senses
Nazreena Rahman1 & Bhogeswar Borah2 Show affiliations
- Kaziranga University, India
- Tezpur University, India
Journal of Computer Science, Volume 17, Issue 6, pp. 556–579 · doi.org/10.3844/jcssp.2021.556.579
Abstract
Finding semantic relatedness score between two sentences is useful in many research areas. Existing relatedness methods do not consider its sense while computing semantic relatedness score between two sentences. In this study, a Word Sense Disambiguation (WSD) method is proposed which is used in finding the sense-oriented sentence semantic relatedness measure. The WSD method is used to find the correct sense of a word present in a sentence. The proposed method uses both the WordNet lexical dictionary and the Wikipedia corpus. The sense-oriented sentence semantic relatedness measure combines edge-based score between words depending the context of the sentence; sense based score which finds sentences having similar senses; as well as word order score. We have evaluated the proposed WSD method on publicly available English WSD corpora. We have compared our proposed sense-oriented sentence semantic relatedness measure on standard datasets. Experimental analysis illustrates the significance of proposed method over many baseline and current systems like Lesk, UKB, IMS, Babelfy.
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Rahman, N. & Borah, B. (2021). An Approach for Finding Semantic Relatedness Score Between Two Sentences Based on their Senses. Journal of Computer Science, 17(6), 556–579. https://doi.org/10.3844/jcssp.2021.556.579
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