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FEATURE ANALYSIS FOR SEMANTIC TEXTUAL SIMILARITY
Dr. K. Anuradha, Himaja Indukuri, Tilak Putta

Published in: International Journal of Current Engineering And Scientific Research ( IJCESR)
Volume- 4, Issue-8, pp.75-79, Aug 2017
DPI :-> 16.10046.IJCESR.2017.V4I8.7579.1870



Abstract
The Semantic similarity is to measure the similarity between two texts. Semantic similarity is measured between two words, sentences, paragraphs and documents. In this paper, text chosen is sentences. Similarity measure is based on semantic and syntactic features. Semantics deals with the same meaning, syntactic deals with rules of syntax. In this paper, analyzed the impact of values syntactic and semantic features in measuring the Semantic Textual Similarity. The experimental work is carried out on SemEval 2017 datasets. The results show that in most of datasets a semantic feature, sent2vec has more impact.

Key-Words / Index Term
Semantic textual similarity, syntactic, semantic, Bagging Model.

How to cite this article
Dr. K. Anuradha, Himaja Indukuri, Tilak Putta , “FEATURE ANALYSIS FOR SEMANTIC TEXTUAL SIMILARITY”, International Journal of Current Engineering And Scientific Research ( IJCESR), 4, Issue-8, pp.75-79, Aug 2017. DPI:16.10046.IJCESR.V4.I8.1870