calculate similarity between nodes

[mousewu]

I am trying to calculate similarity coefficients between nodes based on node embedding vectors obtained from graphwave algorithm. However, the calculated distance between node embedding vectors is very small, e.g. between 0 and 0.01. Hence, the similarity is quite close to 1 for all node pairs. Do you have any suggestion on how to solve this problem? I use the following codes to calculate the distance and similarity:

distance = sc.spatial.distance.euclidean(chi[0,:],chi[1,:]) similarity = 1.0/(1.0+distance)

[Fungker]

hello, i got same quension with you, i want to use these vectors to calculate distance but the pwrformance is not good as Node2vec,we can disscuss this together.

[mousewu]

hello, i got same quension with you, i want to use these vectors to calculate distance but the pwrformance is not good as Node2vec,we can disscuss this together.

Ok, but Node2vec is more computational complex for large graph.

[donnate]

Hi,

If the similarity is too small, then you might want to try another more discriminative distance(such as e^{-S_{ij}/s^2}, and choose an appropriate bandwidth). You might have to play around with the scales to try to get higher contrast between roles. I don't have that much experience with Node2Vec, so I wouldnt be able to give you any advice on that unfortunately.