elasticsearchHow can I use Elasticsearch KNN to find similar documents?
K Nearest Neighbors (KNN) is a machine learning algorithm used for finding similar documents in an Elasticsearch index. It works by computing the similarity between documents using a distance metric such as Euclidean or cosine distance. The algorithm then returns the K nearest neighbors to a given document.
Example code
GET /my_index/_search
{
"query": {
"knn": {
"my_field": {
"vector": [1,2,3],
"k": 10
}
}
}
}
This example code searches the index my_index
for documents similar to the given vector [1,2,3], and returns the 10 nearest neighbors.
The code consists of several parts:
- The
GET
command which specifies the index to search. - The
query
section, which contains theknn
query with themy_field
field containing the vector to search, and thek
parameter specifying the number of nearest neighbors to return.
For more information on using KNN in Elasticsearch, please refer to the Elasticsearch KNN documentation.
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