How does a bag of words model work?
Instruction: Describe the concept of a bag of words model and its application in NLP.
Context: This question evaluates the candidate's knowledge of simple text representation models.
Updated
Example Answer
A bag-of-words model represents a document by the words it contains and usually their counts, while ignoring word order. The output is often a sparse vector where each dimension corresponds to a vocabulary term.
It is simple and surprisingly effective for some classification and retrieval tasks, but it loses syntax, sequence, and nuance. That is its core tradeoff: easy to build and interpret, but weak at capturing deeper language structure.
Common Poor Answer
A weak answer says bag of words stores the important words and misses that it discards word order and context.