A digital textbook optimization system and method based on user interaction behavior

Abstract

The application discloses a digital textbook optimization system and method based on user interaction behavior, and relates to the technical field of path optimization. A textbook knowledge graph is constructed through acquired digital textbooks; nodes in the textbook knowledge graph are aggregated to obtain a graph subset, the topological potential of the graph subset is calculated, and sorting is performed according to the topological potential; nodes in the graph subset with high topological potential are selected to form an initial set, an initial path is generated through an LHK algorithm, path optimization is performed using a self-adaptive large neighborhood search algorithm according to the initial path, and an optimal path is obtained; and the digital textbook is optimized through the optimal path. The method uses the self-adaptive large neighborhood search algorithm in the knowledge graph, introduces specific user interaction behavior data to adjust the learning path in real time, calculates the topological potential of each knowledge point in the knowledge graph, accurately evaluates the priority and learning difficulty of the knowledge point in the learning path, and improves the accuracy and efficiency of textbook optimization.

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