In recent years, knowledge graph has been widely applied to organize data in a uniform way and enhance many tasks that require knowledge.For example, it has been widely used in the field of e-commerce.However, such knowledge services usually include tedious data selection and model design for knowledge infusion, which might bring inappropriate results.Thus, to solve this problem, the method of first pre-training then providing knowledge vector service was put forward, and a pre-trained knowledge graph model (PKGM) was proposed for our billionscale e-commerce product knowledge graph, providing item knowledge services in a uniform way for embeddingbased models without accessing triple data in the knowledge graph.PKGM was tested in three knowledge-related tasks including item classification, same item identification, and recommendation.Experimental results show PKGM successfully improves the performance of each task.
