Causal time sequence double-enhancement knowledge tracking method based on hypergraph clustering

The invention discloses a causal time sequence double-enhancement knowledge tracking method based on hypergraph clustering, and the method comprises the steps: obtaining a data set generated in an online learning process of a learner, and determining the interaction information of exercises; performing hypergraph clustering processing according to the exercise interaction information, and constructing a global knowledge dictionary; according to the global knowledge dictionary, constructing a causal time sequence double-enhancement knowledge tracking model based on front door adjustment logic and learning continuity; and obtaining a current knowledge state and current exercise information of a to-be-predicted object, and generating an answer information prediction result of the to-be-predicted object according to the causal time sequence double-enhancement knowledge tracking model. The method is high in efficiency and can be widely applied to the technical field of computers. 本发明公开了一种基于超图聚类的因果时序双增强知识追踪方法，包括：获取