Hello, I would be so grateful if someone can kindly clarify this for me. For a while, i read about knowledge graph and graph embedding; I learnt that firstly people build knowledge graph/property graph to power Machine learning followed by representing them in low-dimensional space using graph embedding. Yes, graph provides great analytics but i read that it is computationally expensive, as a result it has to be converted in low dimension. Beside context, what is the benefit of network based machine learning as compared to traditional machine learning?
Thank you so much for your time, perhaps my question is wrong but this can really help me a lot.