link prediction?

Hi,

I have been thinking about using NSL in the context of link prediction. It can definitely be reframed as a classification problem I believe. The only thing I am wondering about is if anyone has thought of an elegant way to add the neighbours (I guess in this case of both nodes which form the link ). Has anyone been working on this?

I guess a decent way of going about it would be changing the parse_example function:

def parse_example(example_proto):
  """Extracts relevant fields from the `example_proto`.

  Args:
    example_proto: An instance of `tf.train.Example`.

  Returns:
    A pair whose first value is a dictionary containing relevant features
    and whose second value contains the ground truth labels.
  """

so, that it can take a pair of examples which are part of a link.

Thanks, George

[ggerogiokas]

Hi,

Yea unfortunately, I have this low on my priority list. Haven’t had time to do this! Though one simple thing you can do is just treat edge embeddings as node embeddings and then you have to redefine the network.

George

On Sun, 26 Apr 2020, 10:56 Shrey, [e-mail] wrote:

@ggerogiokas https://github.com/ggerogiokas I am also interested in this aspect of NSL. Did you make any progress on this idea??

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[csferng]

Closing this issue for now due to inactivity. Feel free to reopen if you have any progress or updates on the link prediction idea.