基于隐语义模型的学生选课推荐算法

陈 钢1; 2; 3; 常 笑1; 2; 3; 胡 枫1; 2; 3

基于隐语义模型的学生选课推荐算法

引用本文：陈钢1,2,3,常笑1,2,3,胡枫1,2,3.基于隐语义模型的学生选课推荐算法[J].计算技术与自动化,2021,(3):88-93

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作者	单位
陈钢1,2,3,常笑1,2,3,胡枫1,2,3	（1.青海师范大学计算机学院, 青海西宁 810008；2.青海省藏文信息处理与机器翻译重点实验室,青海西宁 810008；3.藏文信息处理教育部重点实验室，青海西宁 810008)

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，提出了一种基于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

Recommended Algorithm for Students Course-choosing Based on Latent Factor Model

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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