TRANSACTIONS-FREQUENCY BASED GRADED LINK-CLASSIFICATION IN GRAPHS - Gavande, Ashish; Kulkarni, Sushil (INFOCOMP Journal of Computer Science, 2022)
Link classification categorises links between nodes of graphs for improved graph learning. This work proposes a novel approach of using the frequency of transactions between nodes to learn affinity for associations and thereby classifies links between nodes. Further, the classification is done for multiple grades of classification and not just as strong/weak links. The model is successfully able to classify links with around 95 percent micro-F1 accuracy on both homogeneous and heterogeneous datasets using a multi-layer perceptron network.