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Mapping nodes to their respective embedded vectors



I have uploaded a adjacency matrix into neo4j and used node2vec to get the embedded vectors.I intend to use this on a machine learning classification problem where I have to add the output class as the last column to this embedded vectors,but I am not sure if the embedded vectors I obtained are in the same order(row-wise) as in the adjacency matrix.How do I make sure of this.Any help here would be highly appreciated.



If you return the nodeId and embeddings from nod2vec, you can then use gds.util.asNode(nodeId).outputClass


Hi,Could you be a bit more specific.I am sorry am new to this.This is my code

with 600 as noOfNodes

unwind range(1,noOfNodes) as index

create(n:Node{id: index})


load csv from "file:///adjmat.csv" as line

with line skip 1

with line, toInteger(line[0]) as startNode, size(line)-1 as noOfRelationships

match(n:Node{id: startNode})

unwind range(1, noOfRelationships) as index

match(m:Node{id: index})


set r.strength = toFloat(line[index])

Used this code to upload my 600*600 adjacent matrix

and den applied node to vec using

CALL gds.graph.project('all',


    {undirected:{type:'*', orientation:'UNDIRECTED'}})

CALL"all", {walksPerNode: 2, embeddingDimension: 16})

And got the embedded vectors(600*16). which I exported as csv.Now i want to add an output class to this embedded vectors which I have in another excel .But I am not sure this is the right way to do it.Hope you understood my problem now