Text Preprocessing DATA-SCIENCE-OPTIMIZE Practice Questions (Page 7)

Questions 31–35

1. 31foundation · easy

   What is the main goal of stop word removal in text preprocessing?

   • ATo eliminate words that appear frequently but carry little semantic meaning
   • BTo split text into individual tokens
   • CTo replace rare words with a special token
   • DTo convert all words to their base form
   Reveal Solution Discussion Select an answer first
2. 32foundation · easy

   Which of the following is an example of a POS tag?

   • ANN (noun)
   • BNUM
   • CURL
   • DSTOP
   Reveal Solution Discussion Select an answer first
4. 33foundation · easy

   What is the typical approach for handling special characters and punctuation in text preprocessing?

   • AConvert them to uppercase
   • BUse them to split the text into sentences
   • CAlways keep them as separate tokens
   • DRemove or replace them with a placeholder token
   Reveal Solution Discussion Select an answer first
5. 34foundation · easy

   What is the purpose of part-of-speech (POS) tagging in NLP?

   • ATo split text into individual tokens
   • BTo assign grammatical tags like noun, verb, or adjective to each token
   • CTo convert text to lowercase
   • DTo remove stop words from the text
   Reveal Solution Discussion Select an answer first
6. 35foundation · easy

   What is an n-gram in the context of NLP?

   • AA single token from the text
   • BA type of stemming algorithm
   • CA list of stop words
   • DA sequence of n tokens from the text
   Reveal Solution Discussion Select an answer first