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4 changes: 4 additions & 0 deletions modules/ROOT/pages/functions/vector.adoc
Original file line number Diff line number Diff line change
Expand Up @@ -35,6 +35,8 @@ For more details, see the {link-vector-indexes}#similarity-functions[vector inde
| Both vectors must be of the same dimension.
| Both vectors must be {link-vector-indexes}#indexes-vector-similarity-cosine[*valid*] with respect to cosine similarity.
| The implementation is identical to that of the latest available vector index provider (`vector-2.0`).
| `vector.similarity.cosine()` returns the neighborhood of nodes along with their respective cosine similarity scores, sorted in descending order of similarity.
The similarity score range from `0` and 1, with scores closer to `1` indicating a higher degree of similarity between the indexed vector and the query vector.
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The similarity score range from `0` and 1, with scores closer to `1` indicating a higher degree of similarity between the indexed vector and the query vector.
The similarity score range from `0` and `1`, with scores closer to `1` indicating a higher degree of similarity between the indexed vector and the query vector.


|===

Expand Down Expand Up @@ -63,6 +65,8 @@ For more details, see the {link-vector-indexes}#similarity-functions[vector inde
| Both vectors must be of the same dimension.
| Both vectors must be {link-vector-indexes}#indexes-vector-similarity-euclidean[*valid*] with respect to Euclidean similarity.
| The implementation is identical to that of the latest available vector index provider (`vector-2.0`).
| `vector.similarity.euclidean()` returns the neighborhood of nodes along with their respective Euclidean similarity scores, sorted in descending order of similarity.
The similarity score range from `0` and 1, with scores closer to `1` indicating a higher degree of similarity between the indexed vector and the query vector.
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Suggested change
The similarity score range from `0` and 1, with scores closer to `1` indicating a higher degree of similarity between the indexed vector and the query vector.
The similarity score range from `0` and `1`, with scores closer to `1` indicating a higher degree of similarity between the indexed vector and the query vector.


|===

Expand Down