Natural Language Processing

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Across
  1. 2. A statistical model used for POS tagging.
  2. 5. Practical uses of NLP technologies in real-world scenarios.
  3. 7. Continuous sequences of n items from a given sample of text.
  4. 8. Systems designed to answer user queries.
  5. 10. Analysis of larger units of language beyond the sentence.
  6. 12. When a word or phrase can have multiple meanings.
  7. 14. The process of converting a word to its base form.
  8. 16. The study of meaning in language.
Down
  1. 1. A subset of machine learning using neural networks for NLP tasks.
  2. 3. The technique of reducing words to their base or root form.
  3. 4. Analyzing feelings or opinions in text.
  4. 6. A large collection of written or spoken texts.
  5. 9. A process of breaking text into individual words or phrases.
  6. 11. The set of rules that governs the structure of sentences.
  7. 13. The study of the structure and form of words.
  8. 15. Assessing the performance of NLP models and techniques.