Combining machine translation and text similarity metrics to identify paraphrases in Turkish
| dc.contributor.author | Soleymanzadeh K. | |
| dc.contributor.author | Karaoglan B. | |
| dc.contributor.author | Metin S.K. | |
| dc.contributor.author | Kişla T. | |
| dc.date.accessioned | 2019-10-26T21:14:53Z | |
| dc.date.available | 2019-10-26T21:14:53Z | |
| dc.date.issued | 2018 | |
| dc.department | Ege Üniversitesi | en_US |
| dc.description | Aselsan;et al.;Huawei;IEEE Signal Processing Society;IEEE Turkey Section;Netas | en_US |
| dc.description | 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 -- 2 May 2018 through 5 May 2018 -- 137780 | en_US |
| dc.description.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. | en_US |
| dc.identifier.doi | 10.1109/SIU.2018.8404633 | |
| dc.identifier.endpage | 4 | en_US |
| dc.identifier.isbn | 9781538615010 | |
| dc.identifier.scopusquality | N/A | en_US |
| dc.identifier.startpage | 1 | en_US |
| dc.identifier.uri | https://doi.org/10.1109/SIU.2018.8404633 | |
| dc.identifier.uri | https://hdl.handle.net/11454/15915 | |
| dc.indekslendigikaynak | Scopus | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
| dc.relation.ispartof | 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 | en_US |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | Machine translation metrics | en_US |
| dc.subject | Paraphrase Identification | en_US |
| dc.subject | Text similarity metrics | en_US |
| dc.title | Combining machine translation and text similarity metrics to identify paraphrases in Turkish | en_US |
| dc.type | Conference Object | en_US |
