how can i get the node's vector after embedding?

[hurun]

thanks your work,its perfect.
i wonder know how to get the node's vector after embedding.

[hurun]

if I want the node 2 vector ,how can i write code, is it that
model.wv.vectors[1]

[hurun]

i have other question about the node.
If the graph structure is changing dynamically, how can you embed only the newly added nodes and not need to process the other nodes so as to save computation

[hurun]

if I want the node 2 vector ,how can i write code, is it that
model.wv.vectors[1]

i do this, use model.wv.get_vector('2'), your code is amazing :)

[eliorc]

Hi, as stated in the docs, the Node2Vec.fit method returns an instance of gensim.models.Word2Vec, you can see in the documentation how to access vectors

But notice, it is stated in the README, all of your nodes will be strings after using Node2Vec.fit, so you should call '2' and not 2

[hurun]

Thanks your repay, i can get the vector now with your helper.

I have a problem about dynamic graph .
that is the node in the graph will continue to add new nodes over time. Can I just do node2vec algorithm for the newly added node and its neighbor, and keep the other nodes unchanged

[eliorc]

Nope, node2vec algorithm cannot be incrementally updated...

[hurun]

Thank you, i will try to read your code and maybe add this function to algorithm.

[eliorc]

Its not about the code, it's about the algorithm, the algorithm is not built for incremental learning

[hurun]

Yes, your right.
I find a paper about incremental updated, maybe can combine into node2vec
here is paper: Inductive Representation Learning On Large Graphs
code:https://github.com/williamleif/GraphSAGE