Abstract:Multi-modal knowledge graph (MMKG) is a new research hotspot in artificial intelligence in recent years. This study provides a construction method for multi-modal domain knowledge graphs to solve the problem that the domain knowledge system of computer science is large and decentralized. Specifically, a systematic MMKG is constructed by crawling the relevant multi-modal data of computer science. However, the construction of an MMKG needs a lot of manpower and material resources. In response, this study trains a model of joint extraction of entities and relations based on the LEBERT model and relation extraction rules and ultimately implements an MMKG of the computer science domain that can automatically extract relation triples.