minor fixes and additions entries

Author: JPryce-Aklundh

modules/ROOT/pages/deprecations-additions-removals-compatibility.adoc

@@ -21,6 +21,91 @@ Replacement syntax for deprecated and removed features are also indicated.
 Cypher 25 was introduced in Neo4j 2025.06 and can only be used on Neo4j 2025.06+ databases.
 Features removed in Cypher 25 are still available on Neo4j 2025.06+ databases either by prepending a query with `CYPHER 5` or by having Cypher 5 as the default language for the database.
 
+[[cypher-deprecations-additions-removals-2025.xx]]
+== Neo4j 2025.xx
+
+=== New in Cypher 25
+
+[cols="2", options="header"]
+|===
+| Feature
+| Details
+
+a|
+label:functionality[]
+label:new[]
+[source, cypher, role="noheader"]
+----
+VECTOR([1.05, 0.123, 5], 3, FLOAT32 NOT NULL)
+----
+
+a| Introduced a `VECTOR` value type that can be stored as xref:indexes/semantic-indexes/vector-indexes.adoc#embeddings[embedding] properties on nodes and relationships and utilized for efficient semantic retrieval using Neo4j's xref:indexes/semantic-indexes/vector-indexes.adoc[vector indexes] and xref:genai-integrations.adoc[GenAI plugin].
+For more information, see xref:values-and-types/vector.adoc[Values and types -> Vectors].
+
+a|
+label:functionality[]
+label:new[]
+[source, cypher, role="noheader"]
+----
+WITH vector([1, 2, 3], 3, INTEGER) AS vector
+RETURN vector, valueType(vector) AS vectorType
+----
+
+a| New xref:functions/vector.adoc#functions-vector[`vector()`] function for the construction of xref:values-and-types/vector.adoc[`VECTOR`] values.
+
+a|
+label:functionality[]
+label:new[]
+[source, cypher, role="noheader"]
+----
+RETURN vector_dimension_count(vector([1, 2, 3], 3, INTEGER)) AS size
+----
+
+a| New xref:functions/vector.adoc#functions-vector_dimension_count[`vector_dimension_count()`] function, which returns the dimension of a xref:values-and-types/vector.adoc[`VECTOR`] value.
+
+a|
+label:functionality[]
+label:new[]
+[source, cypher, role="noheader"]
+----
+RETURN vector_distance(vector([1, 2, 3], 3, INT), vector([1, 2, 4], 3, INT), COSINE) AS distance
+----
+
+a| New xref:functions/vector.adoc#functions-vector_distance[`vector_distance()`] function, which returns the distance between two xref:values-and-types/vector.adoc[`VECTOR`] values based on the selected `vectorDistanceMetric` algorithm.
+
+a|
+label:functionality[]
+label:new[]
+[source, cypher, role="noheader"]
+----
+RETURN vector_norm(vector([1.0, 5.0, 3.0, 6.7], 4, FLOAT), EUCLIDEAN) AS norm
+----
+
+a| New xref:functions/vector.adoc#functions-vector_norm[`vector_norm()`] function, which returns the distance between the given vector and an origin vector, which is a vector with the same dimension with all coordinates set to zero, calculated using the specified `vectorDistanceMetric`.
+
+|===
+
+=== Updated in Cypher 25
+
+[cols="2", options="header"]
+|===
+| Feature
+| Details
+
+a|
+label:functionality[]
+label:updated[]
+[source, cypher, role="noheader"]
+----
+RETURN toFloatList(Vector([1, 2, 3], 3, INTEGER64)),
+       toIntegerList(Vector([1, 2, 3], 3, INTEGER8)),
+       vector.similarity.cosine(vector([3, 5, 7], 3, INT), vector([-1, -2, -3], 3, INT)),
+       vector.similarity.euclidean(vector([3, 5, 7], 3, INT), vector([-1, -2, -3], 3, INT))
+----
+
+a| The xref:functions/list.adoc#functions-tofloatlist[`toFloatList()`], xref:functions/list.adoc#functions-tointegerlist[`toIntegerList()`], xref:functions/vector.adoc#functions-similarity-cosine[`vector.similarity.cosine()`], and xref:functions/vector.adoc#functions-similarity-euclidean[`vector.similarity.euclidean()`] functions now accept `VECTOR` values as input arguments.
+|===
+
 [[cypher-deprecations-additions-removals-2025.06]]
 == Neo4j 2025.06
 

modules/ROOT/pages/expressions/predicates/type-predicate-expressions.adoc

@@ -40,7 +40,7 @@ RETURN val, val IS :: INTEGER AS isInteger
 
 [role=label-new-2025.xx]
 [[type-predicate-vector]]
-=== VECTOR values
+=== Vector values
 
 Whilst it is not possible to store a xref:values-and-types/vector.adoc[`VECTOR`] value without a coordinate type and dimension, it is possible to use the `VECTOR` supertype (encompassing all combinations of `VECTOR<TYPE>(DIMENSION)`) in type predicate expressions.
 

modules/ROOT/pages/functions/vector.adoc

@@ -261,7 +261,7 @@ RETURN vector_dimension_count(vector([1, 2, 3], 3, INTEGER)) AS size
 
 .Details
 |===
-| *Syntax* 3+| `vector_dimension(vector1, vector2, vectorDistanceMetric)`
+| *Syntax* 3+| `vector_distance(vector1, vector2, vectorDistanceMetric)`
 | *Description* 3+| Returns a `FLOAT` representing the distance between the two vector values based on the selected `vectorDistanceMetric` algorithm.
 .4+| *Arguments* | *Name* | *Type* | *Description*
 | `vector1` | `VECTOR` | The first vector.

modules/ROOT/pages/values-and-types/vector.adoc

@@ -9,7 +9,7 @@ Cypher supports the construction of a `VECTOR` value that can be stored as xref:
 [[vector-type]]
 == The vector type
 
-The `VECTOR` type is a fixed-length, ordered collection of of numeric coordinate values (`INTEGER` or `FLOAT`) stored as a single unit.
+The `VECTOR` type is a fixed-length, ordered collection of numeric coordinate values (`INTEGER` or `FLOAT`) stored as a single unit.
 It is defined by its dimension, which sets how many numeric values it holds, and its coordinate type, which specifies the specific numeric data type for those numbers.
 Each numeric value in the list represents a coordinate along one of the vector’s defined dimensions.
 The coordinate type controls the type of each coordinate in the `VECTOR`, influencing precision and storage size.