虚拟病人模拟器推荐系统的开发

D. Reidel, P. R. Barros, S. Rigo, M. Bez
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引用次数: 0

摘要

本文提出了一个临床案例和资料的推荐系统,可以帮助学生在学习过程中。实验涉及到协作过滤器和基于内容的过滤器以及三种混合方法的开发。使用预测和分类任务的准确性指标对系统进行定性评估。所得结果在协同滤波器上具有很好的应用价值。
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Development of a Recommender System to the Virtual Patient Simulator Health Simulator
This paper presents a recommender system on clinical cases and materials that may help the student in the learning process. The experiment involves the development of collaborative and content based filters and also three hybrid methods. The system was qualitatively evaluated, using accuracy metrics in prediction and classification tasks. The obtained results show promising values on the collaborative filters.
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