Find similarity between two node clusters that are not connected

Neo4j Graph Platform Graph Algorithms/Graph Data Science
1

Hello, I have data structured in a way as seen in the image below:

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image2159×2888 328 KB

There are two people that have distinct interactions. Bob had a phone call, an order, received an email, and had a website visit. John's interactions were two orders, received an email, and had a website visit.

These two "Person" nodes are not connected by relationships, but I'd like to compute the similarity between them. After some research, there are graph similarity algorithms but those seem to mostly rely on relationships.

Is there a way to compute similarity between nodes based on Labels?

In this case, Bob & John would be roughly 75% similar as they share 3 node labels (Order, Email, WebsiteVisit).

Thank you!

2

Hi Henry:

CALL gds.nodeSimilarity.stream('myGraph')
YIELD node1, node2, similarity
RETURN gds.util.asNode(node1).name AS Person1, gds.util.asNode(node2).name AS Person2, similarity
ORDER BY similarity DESCENDING, Person1, Person2

Details about the above can be seen here. Node Similarity - Neo4j Graph Data Science

You will want to make sure that the graph projection you are using contains the nodes and relationships you note in your question above.

3

I suppose you could compute the Jaccard Similarity measure between each pair of Person nodes using your definition of similar.

Applying the definition to your use case, I believe you get the following:
Jaccard Similarity Score = (Total number of connected nodes with labels in common)/(Total number of different labels among connected nodes for the two Person nodes)

4

If you just generally want to compare them for a "diff" you can also look apoc.diff.nodes