A learning method and device based on association rules and dynamic path planning
By combining association rule mining and dynamic path planning with LSTM and gate mechanisms, the problem of inaccurate learning path planning in online education systems is solved, enabling accurate prediction of personalized learning paths and systematic construction of knowledge structures, thereby improving learning efficiency.
CN116955443BActive Publication Date: 2026-06-09SOUTH CHINA NORMAL UNIV
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SOUTH CHINA NORMAL UNIV
- Filing Date
- 2023-06-13
- Publication Date
- 2026-06-09
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Figure CN116955443B_ABST
Abstract
The application relates to a learning method and device based on association rules and dynamic path planning, wherein the learning method based on association rules and dynamic path planning improves an existing neural network model through an LSTM and a gate mechanism, controls memory and forgetting, and prevents gradient explosion and gradient disappearance problems. Similarity and correlation between a current learner and a corresponding user group are calculated first, and then the similarity and correlation are used as prior data of the LSTM to optimally plan a learning path of the learner, and an optimal user learning path of the current learner is generated in combination with a knowledge graph. Since the gate mechanism is introduced, the influence of features before the current time on the next time state can be retained, the next learning state of the user is more accurate, long-time path prediction results are more accurate, and the obtained learning path is more perfect.
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Citation Information
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