What is vector search?
An introduction to vector search/nearest neighbors.
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An introduction to vector search/nearest neighbors.
Last updated
Was this helpful?
Assumed Knowledge: Vectors Target Audience: General developers Reading Time: 3 minutes
What is vector search?
Vector search is the process of finding the most similar vectors to itself. If you are unfamiliar with vectors, I recommend reading about them .
Although we initially used the analogy of vectors as fingerprints in our introduction, vectors actually have additional properties that allow them to be useful in practical applications. These include:
Similar data have similar vectors.
You can measure the similarity of these vectors statistically in a number of different ways.
Why is vector search important?
The most common algorithms that are used are called nearest neighbor algorithms. You can read more about them .
If you can find similar vectors based on the data - this means, you can provide different ways of linking data in ways individuals may have never considered. Linguistically - you can now link sentences based on semantics as opposed to relying on co-occurrences of words (used in traditional word search). Similarly, for image search, you can use reverse image search and personalised image search -- allowing for better recommendations for searches. If you are interested in vector search applications, you can read about them .
