An Interpretable Hypergraph Model for Resume-Job Matching Decision making

Resume-job matching is a crucial subject in the field of human resources (HR). However, existing models and methods lack the capability to learn representations of higher-order interactions and offer interpretability. To overcome this limitation, we introduce an Interpretable Hypergraph model for Resume-Job Matching (IHRJM) framework, which leverages hypergraph representation learning and a learnable factual reasoning model. The goal of the IHRJM framework is to provide precise matching results for resume-job matching while also generating interpretable insights to assist both job seekers and employers in reaching mutually satisfying HR goals.