Semantic similarity between Turkish and European languages using word embeddings

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buir.contributor.authorŞenel, Lütfü Kerem
buir.contributor.authorÇukur, Tolga
dc.contributor.authorŞenel, Lütfü Keremen_US
dc.contributor.authorYücesoy, V.en_US
dc.contributor.authorKoç, A.en_US
dc.contributor.authorÇukur, Tolgaen_US
dc.coverage.spatialAntalya, Turkeyen_US
dc.date.accessioned2018-04-12T11:45:01Z
dc.date.available2018-04-12T11:45:01Z
dc.date.issued2017en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.departmentNational Magnetic Resonance Research Center (UMRAM)en_US
dc.departmentInterdisciplinary Program in Neuroscience (NEUROSCIENCE)en_US
dc.departmentAysel Sabuncu Brain Research Center (BAM)en_US
dc.descriptionDate of Conference: 15-18 May 2017en_US
dc.descriptionConference Name: IEEE 25th Signal Processing and Communications Applications Conference, SIU 2017en_US
dc.description.abstractRepresentation of words coming from vocabulary of a language as real vectors in a high dimensional space is called as word embeddings. Word embeddings are proven to be successful in modelling semantic relations between words and numerous natural language processing applications. Although developed mainly for English, word embeddings perform well for many other languages. In this study, semantic similarity between Turkish (two different corpora) and five basic European languages (English, German, French, Spanish, Italian) is calculated using word embeddings over a fixed vocabulary, obtained results are verified using statistical testing. Also, the effect of using different corpora, and additional preprocess steps on the performance of word embeddings on similarity and analogy test sets prepared for Turkish is studied.en_US
dc.identifier.doi10.1109/SIU.2017.7960365en_US
dc.identifier.urihttp://hdl.handle.net/11693/37594
dc.language.isoTurkishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/SIU.2017.7960365en_US
dc.source.titleProceedings of the IEEE 25th Signal Processing and Communications Applications Conference, SIU 2017en_US
dc.subjectNatural language processingen_US
dc.subjectSemantic similarity between languagesen_US
dc.subjectWord embeddingsen_US
dc.subjectLinguisticsen_US
dc.subjectModeling languagesen_US
dc.subjectSemanticsen_US
dc.subjectEuropean languagesen_US
dc.subjectHigh dimensional spacesen_US
dc.subjectSemantic relationsen_US
dc.titleSemantic similarity between Turkish and European languages using word embeddingsen_US
dc.title.alternativeTürkçe ile Avrupa dilleri arasındaki anlamsal benzerliğin kelime temsilleri ile gösterimien_US
dc.typeConference Paperen_US

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Department of Electrical and Electronics Engineering
Aysel Sabuncu Brain Research Center (BAM)
National Magnetic Resonance Research Center (UMRAM)