Common Neighbors
This feature is not available in GDS Sessions. |
Common neighbors captures the idea that two strangers who have a friend in common are more likely to be introduced than those who don’t have any friends in common.
This feature is in the alpha tier. For more information on feature tiers, see API Tiers.
History and explanation
It is computed using the following formula:
where N(x)
is the set of nodes adjacent to node x
, and N(y)
is the set of nodes adjacent to node y
.
A value of 0 indicates that two nodes are not close, while higher values indicate nodes are closer.
The library contains a function to calculate closeness between two nodes.
Syntax
RETURN gds.alpha.linkprediction.commonNeighbors(node1:Node, node2:Node, {
relationshipQuery:String,
direction:String
})
Name | Type | Default | Optional | Description |
---|---|---|---|---|
|
Node |
null |
no |
A node |
|
Node |
null |
no |
Another node |
|
String |
null |
yes |
The relationship type used to compute similarity between |
|
String |
BOTH |
yes |
The relationship direction used to compute similarity between |
Common Neighbors algorithm sample
CREATE
(zhen:Person {name: 'Zhen'}),
(praveena:Person {name: 'Praveena'}),
(michael:Person {name: 'Michael'}),
(arya:Person {name: 'Arya'}),
(karin:Person {name: 'Karin'}),
(zhen)-[:FRIENDS]->(arya),
(zhen)-[:FRIENDS]->(praveena),
(praveena)-[:WORKS_WITH]->(karin),
(praveena)-[:FRIENDS]->(michael),
(michael)-[:WORKS_WITH]->(karin),
(arya)-[:FRIENDS]->(karin)
MATCH (p1:Person {name: 'Michael'})
MATCH (p2:Person {name: 'Karin'})
RETURN gds.alpha.linkprediction.commonNeighbors(p1, p2) AS score
score |
---|
1.0 |
We can also compute the score of a pair of nodes based on a specific relationship type.
FRIENDS
relationships: MATCH (p1:Person {name: 'Michael'})
MATCH (p2:Person {name: 'Karin'})
RETURN gds.alpha.linkprediction.commonNeighbors(p1, p2, {relationshipQuery: "FRIENDS"}) AS score
score |
---|
0.0 |