Which method uses a sample of documents labeled by humans to learn which words are associated with specific categories?

Which method uses a sample of documents labeled by humans to learn which words are associated with specific categories?

• A. Machine Learning
• B. Feature Extraction
• C. Dictionary (Heuristic)
• D. Bag of Words

Answer: (A)

Learning from labeled documents is a supervised learning approach in natural language processing. By using examples where humans have assigned categories, a model learns statistical patterns that link word usage to those categories. This enables the model to predict the category of new documents based on what it has learned about which words tend to appear in which categories. The other options describe ways to represent text or apply predefined rules rather than letting a model learn from labeled data; they don’t inherently involve learning word-category associations from labeled examples.

Learning from labeled documents is a supervised learning approach in natural language processing. By using examples where humans have assigned categories, a model learns statistical patterns that link word usage to those categories. This enables the model to predict the category of new documents based on what it has learned about which words tend to appear in which categories. The other options describe ways to represent text or apply predefined rules rather than letting a model learn from labeled data; they don’t inherently involve learning word-category associations from labeled examples.