Classification of Semantic Similarity Technique between Word Pairs using Word Net
Atul Gupta1, Krishan Kumar Goyal2
1Atul Gupta*, Department of Computer Science and Engineering, Pranveer Singh Institute of Technology, Kanpur, India .
2Dr. Krishan Kumar Goyal, Computer Application, Raja Balwant Singh Management Technical Campus, Agra, India.
Manuscript received on November 22, 2019. | Revised Manuscript received on December 15, 2019. | Manuscript published on December 30, 2019. | PP: 4397-4402 | Volume-9 Issue-2, December, 2019. | Retrieval Number: B2961129219/2019©BEIESP | DOI: 10.35940/ijeat.B2961.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The concept of relevancy is a most blazing topic in information regaining process. In the last few years there is a drastically increase the digital data so there is a need to increase the accuracy of information regaining process .Semantic Similarity measure the similarity between word-pair by using WordNet as ontology.We have analyzed the different category of semantic similarity algorithm to compute semantic closeness between word-pair and evaluate its value by using WordNet.We have compared various algorithms on Miller- Charles data set of 30 word-pair is used to rank them category wise.
Keywords: Semantic similarity, Semantic closeness, Word Net, Least common subsumer.