With the rapid development of AI technologies, artificial intelligence evolves from perceptual intelligence to cognitive intelligence and machines have been endowed with various cognitive abilities, including knowledge representation, logical reasoning and self-judgement. As the basic technology for cognitive intelligence, knowledge graphs (KG) have gradually become one of the core technologies driving the next generation of artificial intelligence. KGs have been widely adopted in many application scenarios such as semantic search, natural language generation, question answering systems, intelligence dialogue systems and personalized recommender systems. KG is a large-scale semantic knowledge base, which encodes a collection of interlinked descriptions of entities with Resource Description Framework triples. KGs can represent rich semantic information in a unified structured way and thus provides a promising perspective for breaking the information barrier in both data representation and semantic cognition between different fields.