Word Representations with Character N-grams Quiz
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Questions and Answers

What is the main limitation of most word embedding techniques mentioned in the text?

  • They lack parameter sharing
  • They ignore the internal structure of words (correct)
  • They are not efficient on large corpora
  • They do not consider morphologically rich languages
  • How did Mikolov et al. (2013b) propose to learn continuous representations of words?

  • By incorporating morphological features (correct)
  • Using feed-forward neural networks
  • By sharing parameters among words
  • By predicting words based on context
  • What is a distinguishing feature of morphologically rich languages like Turkish and Finnish?

  • They contain many word forms that occur rarely (correct)
  • They have very simple grammatical structures
  • They lack inflectional forms for verbs
  • They do not benefit from character level information
  • What did Alexandrescu and Kirchhoff (2006) introduce to improve modeling of rare words?

    <p>Factored neural language models</p> Signup and view all the answers

    In contrast to some other methods, what does the approach proposed in the text not rely on for deriving word representations?

    <p>Morphological decomposition of words</p> Signup and view all the answers

    What is a limitation of popular models that learn word representations?

    <p>They ignore the morphology of words.</p> Signup and view all the answers

    In the proposed approach based on the skipgram model, how are words represented?

    <p>As the sum of character n-gram representations.</p> Signup and view all the answers

    What advantage does the new method have in training models on large corpora quickly?

    <p>It represents words using character n-grams.</p> Signup and view all the answers

    How are word representations evaluated in the study mentioned?

    <p>By comparing to morphological word representations.</p> Signup and view all the answers

    What is the main historical source of continuous representations of words in natural language processing?

    <p>Rumelhart et al., 1988</p> Signup and view all the answers

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