Rural medical search algorithm on heterogeneous information network with attribute equity

In recent years, rural medical search on heterogeneous information network has attracted more and more attention, and has been widely used in graph analysis. However, the existing rural search problems on heterogeneous information networks do not consider the fairness of attributes on subgraphs. By combining attribute fairness with kPcore mining on heterogeneous information networks, a maximum core mining problem on heterogeneous information networks based on attribute fairness is proposed. To solve this problem, a traversal methodwith vertex sign method is proposed to improve the efficiency of obtaining P_neighbor with high points. A large number of experiments on heterogeneous information network data sets prove the effectiveness and efficiency of the proposed method.