Separating Returned Nodes

[andy_hegedus]

Hi,
The result from a simple query shows three groups of green nodes. Group A is only connected to left blue node, Group B is only connected to the right blue node, and Group C is connected to both.

MATCH  p=(c:cpc)-[:Classified_as]-(a:patent{num:9698021})-[:Classified_as]-(n:cpc)-[:Classified_as]-(b:patent{num:7950348})-[:Classified_as]-(x:cpc)
return p

What is the most straightforward way of defining the three group? (Note: the green-green connection for this question)
c variable should contain all nodes connected to the left blue node including those in n
n variable should contain the shared nodes
x variable should contain all connected to the right blue node including those in n.

What I am interested in (think Venn Diagram)
n
(c-n)
(x-n)
Andy

[david_allen]

To define these groups node-for-node exactly how you like may be very difficult to do without simply hand-labeling them.

But the general problem space you're in is made for community detection algorithms. I recommend taking a look at this page and playing with these approaches, because taking a big graph and partitioning it into multiple different groups or "communities" is just fundamentally what these algorithms do.

Will they do it exactly as you want? Questionable -- but if you read the algorithm descriptions, you can make the right algorithm choice and probably get very close to what you want on big datasets.

Neo4j Graph Database Platform

Community detection algorithms - Neo4j Graph Data Science

This chapter provides explanations and examples for each of the community detection algorithms in the Neo4j Graph Data Science library.