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

Küçük Resim Yok

Tarih

2018

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Institute of Electrical and Electronics Engineers Inc.

Erişim Hakkı

info:eu-repo/semantics/closedAccess

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. © 2018 IEEE.

Açıklama

Aselsan;et al.;Huawei;IEEE Signal Processing Society;IEEE Turkey Section;Netas
26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 -- 2 May 2018 through 5 May 2018 -- 137780

Anahtar Kelimeler

Machine translation metrics, Paraphrase Identification, Text similarity metrics

Kaynak

26th IEEE Signal Processing and Communications Applications Conference, SIU 2018

WoS Q Değeri

Scopus Q Değeri

N/A

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