适应性学习路径推荐算法及应用研究

Recommendation Algorithm and Application of Adaptive Learning Path

在适应性学习路径推荐中，推荐算法起着至关重要的作用。本研究从算法性质的角度归类，将学习路径推荐系统中的推荐算法归为三大类：智能优化算法、数据挖掘算法以及基于知识的推荐算法。结合已开发的学习路径推荐系统，本文从算法性能、学习路径推荐中考虑的因素及算法应用三方面进行比较与分析，总结出上述推荐算法在学习路径推荐中的应用策略和应用中的优势及不足，最后探讨了学习路径推荐的实践应用价值，以期为适应性学习路径推荐领域的研究提供有价值的参考与借鉴。

In the adaptive learning path recommendation， the recommendation algorithm plays a vital role. From the perspective of the nature of algorithm， the recommendation algorithm in learning path recommendation system are grouped into three categories: swarm intelligence optimization algorithm， data mining algorithms and knowledge-based recommendation algorithm. Combined with the developed recommendation system， the paper compared and analyzed from three aspects including performance of the algorithm， the parameter settings in the learning path recommendation and the application. the paper summarized the application strategies of relevant algorithm in the learning path recommendation， as well as the strengths and weaknesses in the application， and discussed the practical application value of learning path recommendation to provide valuable information and reference for research in the field of adaptive learning path recommendation.