Projection modeling for algorithms

You've learned how to create projectionsiFull definition for projection (opens in a new tab)An in-memory copy of part of your database that graph algorithms run against. You choose which nodes and relationships it holds. and how to configure algorithms. Now it's time to connect these skills: modeling projections specifically for the questions you want your algorithms to answer.

In Module 2, you discovered that the same data can be projected in different ways—monopartiteiFull definition for monopartite graph (opens in a new tab)A graph in which every node is the same kind of thing, so relationships connect like to like., bipartiteiFull definition for bipartite graph (opens in a new tab)A graph with two kinds of node, where every relationship joins one kind to the other and never two of the same kind., or multipartiteiFull definition for multipartite graph (opens in a new tab)A graph with three or more kinds of node, where relationships only ever join nodes of different kinds.. Each projection reveals different patternsiFull definition for pattern (opens in a new tab)A graph structure written in Cypher, such as a node joined to another node by a relationship., and the right projection depends on your analytical question.