juniorNLP
What is bag-of-words model?
Updated May 17, 2026
Short answer
Bag-of-words represents text as word frequency vectors ignoring grammar and order.
Deep explanation
BoW converts text into a sparse vector where each dimension corresponds to a word in the vocabulary. It captures frequency but loses syntax and context.
Real-world example
Used in simple spam classification systems.
Common mistakes
- Ignoring word order limitations.
Follow-up questions
- How is TF-IDF different from BoW?
- Why is BoW inefficient?