Combining machine translation and text similarity metrics to identify paraphrases in Turkish
Bildiriler > Tam Metin Bildiri
Yazarlar: Katira Soleymanzadeh, Bahar Karaoglan, Senem Kumova Metin, Tarık KIŞLA
2018 26th Signal Processing and Communications Applications Conference (SIU), , , Uluslararası, Tam Metin Bildiri, ss 1-4
Özet
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.