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qdrant-landing/content/course/essentials/day-3/sparse-vectors.md
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Comparing two sparse representations, you'd be usually interested in how much they agree on the same features/objects (e.g., the same movie rating).
The **dot product** distance metric, introduced in the **day 1** (*Vector Search Fundamentals/Distance Metrics*), is a perfect fit for measuring the similarity between sparse representations.
The **dot product** distance metric, introduced in the **Day 1** (*Vector Search Fundamentals/Distance Metrics*), is a perfect fit for measuring the similarity between sparse representations.
It multiplies corresponding dimensions and summes the results.
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