Text Preprocessing DATA-SCIENCE-OPTIMIZE Practice Questions (Page 1)

Questions 1–5

1. 1foundation · easy

   What is a bigram?

   • AA sequence of three tokens
   • BA single token
   • CA sequence of two tokens
   • DA list of all words in the text
   Reveal Solution Discussion Select an answer first
2. 2foundation · easy

   Which of the following is an example of standardizing an abbreviation in text preprocessing?

   • AConverting 'e.g.' to 'for example'
   • BConverting 'Hello' to 'hello'
   • CSplitting 'hello world' into 'hello' and 'world'
   • DRemoving the word 'the'
   Reveal Solution Discussion Select an answer first
4. 3foundation · easy

   In a text preprocessing pipeline, what is the primary purpose of tokenization?

   • ATo reduce words to their base or root form
   • BTo convert all characters to lowercase
   • CTo split text into individual units such as words or punctuation marks
   • DTo remove common words that carry little meaning
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5. 4foundation · easy

   Which of the following words would most likely be removed during stop word removal?

   • Aalgorithm
   • Bthe
   • Cmodel
   • Ddata
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6. 5foundation · easy

   What is the purpose of padding in sequence preprocessing?

   • ATo ensure all sequences have the same length by adding a padding token
   • BTo split text into tokens
   • CTo remove tokens from longer sequences
   • DTo convert tokens to lowercase
   Reveal Solution Discussion Select an answer first