What is Sparse Retrieval?
A retrieval method that uses traditional term-matching techniques, such as TF-IDF or BM25, to find relevant documents.
More about Sparse Retrieval:
Sparse Retrieval is a traditional information retrieval method that relies on term-matching algorithms like TF-IDF (Term Frequency-Inverse Document Frequency) or BM25. These techniques rank documents based on the presence and importance of terms in the query.
While sparse retrieval is less effective for understanding semantics compared to dense retrieval, it remains efficient and interpretable, making it useful for applications where exact term matching is sufficient or preferred.
Frequently Asked Questions
How does sparse retrieval compare to dense retrieval?
Sparse retrieval focuses on exact term matching, while dense retrieval captures semantic relationships.
What are common algorithms used in sparse retrieval?
Algorithms like BM25 and TF-IDF are foundational to sparse retrieval systems.
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