ProNE
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Source code and dataset for IJCAI 2019 paper "ProNE: Fast and Scalable Network Representation Learning"
Hi - I installed ProNE (python 2.7) and was able to train embeddings for the PPI example with the command: python proNE.py -graph data/PPI.ungraph -emb1 emb/PPI_sparse.emb -emb2 emb/PPI_spectral.emb -dimension 128...
My dataset consist graphs with weighted edges. How can I use ProNE for weighted graph embedding? Can I replcace the element of "1" in adjacent matrix with the corresponding weights...
Hi, I just read the original paper on ProNE and wanted to test it on the CTU-13 dataset which consist of network communication data between IPs and I planned to...
Dear Authors, I have a question about the performance of the Wikipedia dataset shown in Table 3 of your paper. I ran your code and successfully reproduced results. However, when...
Just as the title, could you submit the version of the youtube.cmty as your paper. The youtube.cmty in the SNAP is not the same as the version in your paper.
I have tested the python code on youtube dataset and prone only costs 390 seconds, impressive! But the memory cost is another important factor I concerned and prone-py uses 12G+...
I'm trying to get embeddings for Elliptic Dataset (https://www.kaggle.com/ellipticco/elliptic-data-set), but the problem that I'm facing is that nodes are transaction ids (please find edges file in the elliptic dataset in...
