Resumen de DeepRank: improving unsupervised node ranking via link discovery

Yi-An Lai, Chin-Chi Hsu, Wen-Hao Chen, Mi-Yen Yeh, Shou-De Lin

• This paper proposes an unsupervised node-ranking model that considers not only the attributes of nodes in a graph but also the incompleteness of the graph structure. We formulate the unsupervised ranking task into an optimization task and propose a deep neural network (DNN) structure to solve it. The rich representation capability of the DNN structure together with a novel design of the objectives allow the proposed model to significantly outperform the state-of-the-art ranking solutions.