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would anyone please explain a practical non scientific example what one could do with this project given a arbitrary and complex graph being fed as an input
by chrisMyzel 7y ago
would anyone please explain a practical non scientific example what one could do with this project given a arbitrary and complex graph being fed as an input
- np_tedious 7y agoI am by no means an expert in this space, but I'm pretty sure the most straightforward answers will be some form of "clustering". Find cliques among personal connections, business networks among companies, etc
- benitorosenberg 7y agoI am the OP. A few examples: 1. DeepWalk: You have the social network of users and for some of them their age. You want to predict the missing age values so that You are able to design a good targeted marketing campaign. The solution that DeepWalk gives: Learn a node level embedding, learn to predict the age based on the embedding, make a prediction for the missing users. 2. Graph2Vec: You have the molecules of hundred thousands of materials. You know that some of them is a carcinogen, while others are not. How can you predict whether a molecule is a carcinogen? The solution that Graph2Vec gives: Learn a graph level embedding, learn to predict the carcinogen / not carcinogen target and predict whether a molecule with unknown status is a carcinogen or not.