An inverted index accesses only documents associated with active terms instead of comparing every dimension. Traditional term weighting and learned sparse models both preserve explicit token-level signals.
Sparse retrieval represents queries and documents with vectors containing mostly zero values, often tied to vocabulary terms.
An inverted index accesses only documents associated with active terms instead of comparing every dimension. Traditional term weighting and learned sparse models both preserve explicit token-level signals.