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.
From the blog

Automate your customer support and marketing with Zapier and SiteSpeakAI
With the power of Zapier's 6000+ available apps and integrations, you can now connect your chatbot to your favorite tools and completely automate every aspect of your customer support and brand marketing.

Herman Schutte
Founder

Revolutionizing University Engagement with AI Chatbots: A Look at SiteSpeakAI
Explore how universities are leveraging AI chatbots to enhance student engagement and streamline administrative tasks. Discover SiteSpeakAI, a tool that trains chatbots on website content to answer visitor queries.

Herman Schutte
Founder