Node Classification through Graph Embedding Techniques

The purpose of this paper is to collate advanced embedding techniques for the classification of nodes with the help of state-of-art technology named JDeep LearningJ, The main agenda of this classification is to predict the most likely labels of nodes in the network. It is considered to be efficient only if the network dimension is reduced before predicting the labels. Hence, the graph embedding technique is used to reduce it to a low-dimensional network. It also helps to capture and preserve the structure of a network. Comparison is done using various available graph embedding techniques to observe the accuracy.