Remove extensive algo description

Author: FlorentinD

graphdatascience/procedure_surface/api/similarity/node_similarity_endpoints.py

@@ -48,9 +48,6 @@ def mutate(
         """
         Runs the Node Similarity algorithm and stores the results as new relationships in the graph catalog.
 
-        The Node Similarity algorithm computes the similarity between nodes based on their neighborhoods,
-        creating new relationships between each node and its most similar neighbors.
-
         Parameters
         ----------
         G : GraphV2
@@ -125,9 +122,6 @@ def stats(
         """
         Runs the Node Similarity algorithm and returns execution statistics.
 
-        The Node Similarity algorithm computes the similarity between nodes based on their neighborhoods,
-        creating new relationships between each node and its most similar neighbors.
-
         Parameters
         ----------
         G : GraphV2
@@ -198,9 +192,6 @@ def stream(
         """
         Runs the Node Similarity algorithm and returns the result as a DataFrame.
 
-        The Node Similarity algorithm computes the similarity between nodes based on their neighborhoods,
-        creating new relationships between each node and its most similar neighbors.
-
         Parameters
         ----------
         G : GraphV2
@@ -274,9 +265,6 @@ def write(
         """
         Runs the Node Similarity algorithm and writes the results back to the database.
 
-        The Node Similarity algorithm computes the similarity between nodes based on their neighborhoods,
-        creating new relationships between each node and its most similar neighbors.
-
         Parameters
         ----------
         G : GraphV2
@@ -350,10 +338,7 @@ def estimate(
     ) -> EstimationResult:
         """
         Estimates the memory requirements for running the Node Similarity algorithm.
-
-        The Node Similarity algorithm computes the similarity between nodes based on their neighborhoods,
-        creating new relationships between each node and its most similar neighbors.
-
+        
         Parameters
         ----------
         G : GraphV2

graphdatascience/procedure_surface/api/similarity/node_similarity_filtered_endpoints.py

@@ -44,10 +44,6 @@ def mutate(
         """
         Runs the Filtered Node Similarity algorithm and stores the results as new relationships in the graph catalog.
 
-        The Filtered Node Similarity algorithm computes the similarity between nodes based on their neighborhoods
-        with customizable source and target node filters, creating new relationships between each node and its
-        most similar neighbors within the filtered subset.
-
         Parameters
         ----------
         G : GraphV2
@@ -128,10 +124,6 @@ def stats(
         """
         Runs the Filtered Node Similarity algorithm and returns execution statistics.
 
-        The Filtered Node Similarity algorithm computes the similarity between nodes based on their neighborhoods
-        with customizable source and target node filters, creating new relationships between each node and its
-        most similar neighbors within the filtered subset.
-
         Parameters
         ----------
         G : GraphV2
@@ -208,10 +200,6 @@ def stream(
         """
         Runs the Filtered Node Similarity algorithm and returns the result as a DataFrame.
 
-        The Filtered Node Similarity algorithm computes the similarity between nodes based on their neighborhoods
-        with customizable source and target node filters, creating new relationships between each node and its
-        most similar neighbors within the filtered subset.
-
         Parameters
         ----------
         G : GraphV2
@@ -291,10 +279,6 @@ def write(
         """
         Runs the Filtered Node Similarity algorithm and writes the results back to the database.
 
-        The Filtered Node Similarity algorithm computes the similarity between nodes based on their neighborhoods
-        with customizable source and target node filters, creating new relationships between each node and its
-        most similar neighbors within the filtered subset.
-
         Parameters
         ----------
         G : GraphV2
@@ -375,10 +359,6 @@ def estimate(
         """
         Estimates the memory requirements for running the Filtered Node Similarity algorithm.
 
-        The Filtered Node Similarity algorithm computes the similarity between nodes based on their neighborhoods
-        with customizable source and target node filters, creating new relationships between each node and its
-        most similar neighbors within the filtered subset.
-
         Parameters
         ----------
         G : GraphV2 | dict[str, Any]