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