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Computational Linguistics and Natural Language Processing
Contributed by: Brennan
  • 1. What is Computational Linguistics?
A) The study of how to program computers to understand human language.
B) A field that combines linguistics and computer science to understand and model natural language.
C) A subfield of biology that analyzes genetic coding in organisms.
D) The process of translating languages using computational algorithms.
  • 2. What is the main challenge in processing human language computationally?
A) Syntax errors.
B) Ambiguity.
C) Data volume.
D) Redundancy.
  • 3. Which type of machine learning is commonly used in NLP?
A) Genetic algorithms.
B) Decision trees.
C) Deep learning.
D) Support vector machines.
  • 4. What does POS tagging stand for in NLP?
A) Part-of-speech tagging.
B) Project object storage.
C) Position-orientation system.
D) Personalized output selection.
  • 5. Book reviews classification is an example of what NLP task?
A) Sentiment analysis.
B) Text classification.
C) Machine translation.
D) Syntactic analysis.
  • 6. Which of the following is an unsupervised learning technique used in NLP?
A) Neural networks.
B) Support vector machines.
C) Decision trees.
D) Clustering.
  • 7. What is the purpose of machine translation in NLP?
A) To automatically translate text from one language to another.
B) To generate new text based on existing content.
C) To analyze the sentiment of a text.
D) To summarize text.
  • 8. Which type of algorithm is commonly used for named entity recognition?
A) Conditional random fields (CRFs).
B) Neural networks.
C) Genetic algorithms.
D) Support vector machines.
  • 9. What is the main objective of information extraction in NLP?
A) To classify sentences into categories.
B) To perform machine translation.
C) To automatically extract structured information from unstructured text.
D) To summarize a text document.
  • 10. Which programming language is commonly used for implementing NLP algorithms?
A) Python.
B) JavaScript.
C) Java.
D) C++.
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