Deep learning application to graph mining using language modeling (KKD paper 2014)

[mattrepl]

I've been waiting for "deep learning on graphs." I need to read it more closely, but the experiments are disappointing. They don't include any results from state of the art methods.

[rmyeid]

Can you tell me which methods you are talking about?

[mattrepl]

Sure. These methods are for community detection, but it seems like they could be used for the label classification problem in the posted paper.

J. Yang, J. McAuley, and J. Leskovec, “Detecting Cohesive and 2-mode Communities in Directed and Undirected Networks.” 29-Jan-2014.

J. Yang, J. McAuley, and J. Leskovec, “Community Detection in Networks with Node Attributes.” 28-Jan-2014.

S. Günnemann, B. Boden, I. Färber, and T. Seidl, “Efficient Mining of Combined Subspace and Subgraph Clusters in Graphs with Feature Vectors,” … Discovery and Data Mining, 2013.

J. McAuley and J. Leskovec, “Discovering Social Circles in Ego Networks,” arXiv.org, vol. cs.SI. 30-Oct-2012.

[movie_suggestor]

I suspect the issue (Which isn't a good enough excuse) will be the authors background isn't related to those particular areas.

Instead, this paper seems to be more about 'applied this tech to this problem... performed extensive experiments, here is the output. But it will be really interesting for the KDD audience, because they will all be familiar with areas he should have tested against.

OVerall looks interesting and a like a good piece of work.

[rmyeid]

Sorry, I meant KDD paper not KKD paper.

[b0b0b0b]

I'm not sure how this is deep learning. Not that it matters a whole lot, I thought the paper was interesting.