Temporal Knowledge Graph Completion

Temporal Knowledge Graph Completion (TKGC) is a technique that extends knowledge graphs over time, aiming to enrich and complete them by predicting missing time-related facts. This technology combines the entity relationships in static knowledge graphs with time series data to accurately model dynamic events and relationships. Its primary goal is to enhance the completeness and timeliness of knowledge graphs, thereby providing more precise services in applications such as intelligent question answering, recommendation systems, and event prediction.