Combining machine translation and text similarity metrics to identify paraphrases in Turkish

Abstract

Paraphrase identification (PI) is to recognize whether given two sentences are restatements of each other or not. In our study we propose an approach that exploits machine translation and text similarity metrics as features for PI. Machine learning algorithms like Support Vector Machine (SVM) with three different kernels, C4.5 Decision tree and Multinomial Naïve Bayes (NB) are trained with these features. We evaluated our system on Parder, Turkish paraphrase corpus. The experimental results show that the proposed approach offers state-of-the-art results. © 2018 IEEE.