Detection of paraphrases for Devanagari languages using support vector machine

Paraphrase is a process of computing the semantic similarity between sentences, which are not lexicographically similar. It relates to the writing a sentence in another form. Though a number of metrics for English language have been proposed in literature, to quantify textual similarity; but none for Devanagari language. Existing system for Indian language paraphrase detection uses lexical similarity are supervised and requires large scale tagged corpus. The proposed method employs SVM learning metrics, based on lexicography similarity with producing output as +1 for paraphrased, −1 for not paraphrased, takes a sentence as input and produces another sentence without changing its semantic. In particular, the system addresses the problem for detection of monolingual text to text similarity for fusion language like Hindi and Marathi, which has complex morphology.

[2]  Nirali Patel,et al.  Hierarchical clustering technique for word sense disambiguation using Hindi WordNet , 2015, 2015 5th Nirma University International Conference on Engineering (NUiCONE).

[3]  D. Uribe Recognition of Paraphrasing Pairs , 2008, 2008 Electronics, Robotics and Automotive Mechanics Conference (CERMA '08).

[4]  Shuai Xu,et al.  A combination of rule and supervised learning approach to recognize paraphrases , 2009, 2009 International Conference on Machine Learning and Cybernetics.

[5]  El-Sayed M. El-Alfy,et al.  Statistical Analysis of ML-Based Paraphrase Detectors with Lexical Similarity Metrics , 2014, 2014 International Conference on Information Science & Applications (ICISA).

[6]  Rupal Bhargava,et al.  BITS_PILANI@DPIL-FIRE2016: Paraphrase Detection in Hindi Language using Syntactic Features of Phrase , 2016, FIRE.

[7]  Deepa Gupta,et al.  ASE@DPIL-FIRE2016: Hindi Paraphrase Detection using Natural Language Processing Techniques & Semantic Similarity Computations , 2016, FIRE.

[8]  Zornitsa Kozareva,et al.  Paraphrase Identification on the Basis of Supervised Machine Learning Techniques , 2006, FinTAL.

[9]  E. Jayabalan,et al.  An Eccentric Approach for Paraphrase Detection Using Semantic Matching and Support Vector Machine , 2014, 2014 International Conference on Intelligent Computing Applications.

[10]  Yusuke Miyao,et al.  Paraphrase Detection Based on Identical Phrase and Similar Word Matching , 2015, PACLIC.