Describe the use of TF-IDF.
Instruction: Explain what TF-IDF stands for and how it is used in NLP.
Context: This question is designed to test the candidate's knowledge of text representation techniques.
Updated
Example Answer
TF-IDF stands for term frequency–inverse document frequency. It is a weighting method that scores how important a term is to a document relative to a corpus. A word gets higher weight when it appears often in a specific document but not too often across all documents.
It is useful for search, document ranking, keyword extraction, and simple text classification baselines because it highlights discriminative terms without needing deep modeling. Even today, it is a strong baseline in many information-retrieval workflows.
Common Poor Answer
A weak answer says TF-IDF counts important words without explaining the balance between within-document frequency and corpus-wide rarity.