Research on the construction of teaching resource recommendation system for ideological and political courses based on big data technology

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Big data improves recommendation accuracy in ideological education, suggesting personalized resource matching.

The system enhances recommendation accuracy for ideological education courses, supporting high educational value.
Experiments show that big data technology leads to more precise matching and personalization of course resources.
The algorithm employs machine learning and NLP for intelligent recommendations with dynamic weight adjustment.
Closed-loop design allows for continuous feedback to refine the ideological content of educational resources.

Jinwei Dong (2025) studied this question.

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