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      Semantic similarity between Turkish and European languages using word embeddings

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      Author
      Şenel, Lütfü Kerem
      Yücesoy, V.
      Koç, A.
      Çukur, Tolga
      Date
      2017
      Source Title
      Proceedings of the IEEE 25th Signal Processing and Communications Applications Conference, SIU 2017
      Publisher
      IEEE
      Language
      Turkish
      Type
      Conference Paper
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      Abstract
      Representation 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.
      Keywords
      Natural language processing
      Semantic similarity between languages
      Word embeddings
      Linguistics
      Modeling languages
      Semantics
      European languages
      High dimensional spaces
      Semantic relations
      Permalink
      http://hdl.handle.net/11693/37594
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/SIU.2017.7960365
      Collections
      • Aysel Sabuncu Brain Research Center (BAM) 207
      • Department of Electrical and Electronics Engineering 3657
      • National Magnetic Resonance Research Center (UMRAM) 213
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