Intelligent recommendation system based on knowledge graph for scientific research teams

With the continuous penetration of information technology into scientific research work, information resources with diverse structures have gathered into the scientific research team. Facing the needs of scientific research workers to manage and utilize scientific research resources, we provide a knowledge recommendation platform for university scientific research teams. In the face of multi-source heterogeneous resources in the scientific research field (such as literature data and work record data), we have established a resource knowledge base based on knowledge graph descriptions. In order to realize the effective recommendation of resources, we use the graph neural network model to design a personalized recommendation module while constantly updating our knowledge resources. After actual testing, our resource platform can better knowledge resources and push knowledge content.