Natural Language Processing (NLP) AIE Practice Questions (Page 8)

Questions 36–38

1. 36foundation · easy

   How do neural language models capture linguistic patterns compared to traditional statistical models?

   • ABy counting the frequency of each word in a corpus
   • BBy storing all possible sentences in a database
   • CBy learning distributed representations of words from large amounts of text
   • DBy using hand-crafted grammar rules exclusively
   Reveal Solution Discussion Select an answer first
2. 37application · medium

   A startup is building a chatbot that must generate coherent responses in customer conversations. They have a large corpus of support tickets and want the model to predict the next word in a sentence. Which approach is most appropriate?

   • AUse a rule-based system that replaces keywords with predefined responses.
   • BUse a bag-of-words model to represent each sentence as a vector.
   • CTrain a neural language model on the corpus to learn word probabilities from context.
   • DApply stemming to the corpus and then use a simple frequency counter.
   Reveal Solution Discussion Select an answer first
3. 38application · medium

   A team is building a next-word prediction feature for a mobile keyboard. They have a large corpus of text messages and want a model that can capture the context of the previous few words to suggest the most likely next word. Which approach is best suited for this task?

   • AA simple stemming algorithm applied to the corpus
   • BA neural language model using an n-gram window of previous tokens
   • CA stop-word removal process that filters out common words
   • DA bag-of-words model that counts word frequencies in the entire corpus
   Reveal Solution Discussion Select an answer first