Text Data Preprocessing and Tokenization
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Questions and Answers

What is the purpose of tokenization in text preprocessing?

  • To convert text into numerical vectors directly
  • To remove all punctuation marks from the text
  • To break up the words in the text into individual tokens (correct)
  • To combine words into phrases for better analysis

    • What is a key step in constructing a vocabulary for text vectorization?

  • Tokenization to form individual tokens (correct)
  • Stemming and lemmatization of words
  • Removing all stopwords from the text
  • Converting text into numerical vectors

    • What does the vocabulary of tokens represent in text preprocessing?

  • The length of each token in the text data
  • The position of each token in the original text
  • The set of all unique tokens occurring in the data (correct)
  • The frequency of each token in the text data

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