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Texts Semantic Similarity Detection Based Graph
Similarity of text documents is important to analyz e and extract useful information from text document s and
generation of the appropriate data. Several cases o f lexical matching techniques offered to determine the similarity between
documents that have been successful to a certain li mit and these methods are failing to find the seman tic similarity between
two texts. Therefore, the semantic similarity appro aches were suggested, such as corpus-based methods and knowledge based
methods e.g., WordNet based methods. This paper, of fers a new method for Paraphrase Identification (PI) in order to,
measuring the semantic similarity of texts using an idea of a graph. We intend to contribute to the or der of the words in
sentence. We offer a graph based algorithm with spe cific implementation for similarity identification that makes extensive use
of word similarity information extracted from WordN et. Experiments performed on the Microsoft research paraphrase corpus
and we show our approach achieves appropriate perfo rmance.
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