Open Knowledge Graph Embedding

Open Knowledge Graph Embedding is a technique that maps entities and relations in a knowledge graph to a low-dimensional vector space, aiming to capture their semantic information through learning the representations of entities and relations. The goal of this technology is to construct efficient and accurate embedding models to support complex graph reasoning and prediction tasks. In practical applications, Open Knowledge Graph Embedding can enhance performance in areas such as information retrieval, recommendation systems, and natural language processing, making it highly valuable.