AWS neptune-analytics documentation change
Summary
Updated the number of supported centrality algorithms from three to four and fixed a typo (nodes's -> node's).
Security assessment
The change updates a count of supported algorithms and corrects grammar. There is no mention of security features, vulnerabilities, or security-related documentation.
Diff
diff --git a/neptune-analytics/latest/userguide/centrality-algorithms.md b/neptune-analytics/latest/userguide/centrality-algorithms.md index 7759f3d00..062b6fdc7 100644 --- a//neptune-analytics/latest/userguide/centrality-algorithms.md +++ b//neptune-analytics/latest/userguide/centrality-algorithms.md @@ -15 +15 @@ In addition to returning centrality data to the client, Neptune Analytics provid -Neptune Analytics supports three centrality algorithms along with their mutate variants: +Neptune Analytics supports four centrality algorithms along with their mutate variants: @@ -17 +17 @@ Neptune Analytics supports three centrality algorithms along with their mutate v - * [degree](./degree.html) – This measures a nodes's centrality by the number of edges connected to it, and can therefore be used to find the most connected nodes in a network. + * [degree](./degree.html) – This measures a node's centrality by the number of edges connected to it, and can therefore be used to find the most connected nodes in a network. @@ -23 +23 @@ Neptune Analytics supports three centrality algorithms along with their mutate v - * [pageRank](./page-rank.html) – This is an iterative algorithm that measures a nodes's centrality by the number and quality of incident edges and adjacent vertices. The centrality of a node connected to a few important nodes may therefore be higher than that of a node connected to many less important nodes. The output of this algorithm is a value that indicates the importance of a given node relative to the other nodes in the graph. + * [pageRank](./page-rank.html) – This is an iterative algorithm that measures a node's centrality by the number and quality of incident edges and adjacent vertices. The centrality of a node connected to a few important nodes may therefore be higher than that of a node connected to many less important nodes. The output of this algorithm is a value that indicates the importance of a given node relative to the other nodes in the graph.