All, We are considering leveraging the concept of subgraphs as an approach for interactively visualizing large quantities of data. The idea is that by aggregating collections of nodes that share some characteristic into a single node, we may be able to reduce a graph's complexity to the point where an entire graph can be displayed on screen and convey useful information to a user. At that point, specific nodes could be expanded to show additional detail. In theory, these subgraphs could be nested for multiple levels.
GraphML already has support for this idea, but not in a way that reduces bandwidth or memory requirements. I think we would prefer to leave the detail of the subgraph out of the xml until such time that a user requests the detail. Otherwise, we would still suffer from sluggish performance and memory constraints. My questions for the group are: 1) Are there any suggestions for how subgraphs might be algorithmically determined? Are there "clustering" algorithms that might be leveraged? 2) Is there a recommended way for storing subgraphs in neo4j? Should additional nodes for the subgraphs be inserted into the graph, with links from the contained nodes back to the subgraph nodes, or are they ways to do this that do not involve altering the graph "schema"; perhaps an attribute-based approach? 3) Any other idea on this train of thought? I do not have a specific use case in mind. I am hoping to identify an approach that could be applied to large numbers of nodes in general. By large graph, I mean one million nodes or more and by manageable graph I mean less than one thousand nodes. Thanks in advance, -Paul Jackson _______________________________________________ Neo4j mailing list [email protected] https://lists.neo4j.org/mailman/listinfo/user
