| 基于隐语义模型的学生选课推荐算法 |
投稿时间：2020-05-20 修订日期：2020-06-09  点此下载全文 |
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| 基金项目:国家自然科学(61663041),青海科技计划项目(2018-ZJ-718)。 |
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| 中文摘要:为了使学生可以准确、合理的进行选修课程,并调动其学习主动性,考虑到学生-课程之间潜在关系,提出一种基于Funk - SVD技术的隐语义模型学生选课推荐算法。本算法使用随机梯度下降法优化损失函数；对选课推荐算法执行过程中的冷启动问题提出了一种处理方案；通过评价指标召回率、准确率以及平衡F分数验证本算法推荐的可行性和有效性,在所收集到的学生选课数据集上进行测试,实验结果表明,该算法具有一定的优势。 |
| 中文关键词:推荐算法 潜在关系 隐语义模型 |
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| RECOMMENDED ALGORITHM FOR STUDENTS COURSE-CHOOSING BASED ON LATENT FACTOR MODEL |
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| Abstract:In order to enable students to take courses correctly and reasonably, and to arouse their enthusiasm of learning, in view of the actual relationship between students and courses, this thesis proposes a latent factor model of recommended algorithm for students on the basis of Funk-SVD technology. This algorithm applies a method of stochastic gradient descent to optimize the loss function; a solution to solve the problem of cold boot during the process of recommended algorithm for students course-choosing is provide accordingly; the feasibility and validity of this kind of recommended algorithm are verified by evaluating the index recall rate, accuracy rate, and balanced F score, testing on the data collected from students" course-choosing. The experimental results show that the algorithm is advantageous. |
| keywords:recommended algorithm actual relationship latent factor model |
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