DocumentCode :
162604
Title :
An Eccentric Approach for Paraphrase Detection Using Semantic Matching and Support Vector Machine
Author :
Vigneshvaran, P. ; Jayabalan, E. ; Kathiravan, A. Vijaya
Author_Institution :
Dept. of Comput. Sci., Gov. Arts Coll., Salem, India
fYear :
2014
fDate :
6-7 March 2014
Firstpage :
431
Lastpage :
434
Abstract :
Paraphrase is the process of writing a sentence in another form. It relates to computing the similarity between sentences which are not lexicographically similar. This paper proposed an efficient method to estimate paraphrase. Specifically this paper defines various word co-occurrence in the sentence measured and its synonyms are also identified using web. By using the algorithm, similarity has been measured. This research focuses on evaluating the paraphrase between the sentences. In this paper, an approach for detecting paraphrase is tested by counting tokens. It processes token matching with the help of synonym of tokens, and produces the result with SVM classifier using Plagiarism detection corpus (PAN). Thus the SVM produces the output as +1 if the given text is paraphrased, - 1 if the given text is not paraphrased. This approach may also be used to identify Plagiarism of documents and to eliminate duplicates in a text repository.
Keywords :
information retrieval; natural language processing; pattern matching; security of data; support vector machines; text analysis; SVM classifier; paraphrase detection; plagiarism detection corpus; semantic matching; support vector machine; text repository; token matching; Measurement; Object oriented programming; Plagiarism; Semantics; Support vector machines; Tagging; POS tagging; Paraphrase; Plagiarism Detection Corpus (PAN); Semantic Matching; Support Vector Machine (SVM); Tokenization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computing Applications (ICICA), 2014 International Conference on
Conference_Location :
Coimbatore
Type :
conf
DOI :
10.1109/ICICA.2014.94
Filename :
6965086
Link To Document :
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