g = new Neo4jGraph('/tmp/neo4j')
// calculate basic collaborative filtering for vertex 1
m = [:]
g.v(1).out('likes').in('likes').out('likes').groupCount(m)
m.sort{a,b -> a.value <=> b.value}
// calculate the primary eigenvector (eigenvector centrality) of a graph
m = [:]; c = 0;
g.V.out.groupCount(m).loop(2){c++ < 1000}
m.sort{a,b -> a.value <=> b.value}