基于深度哈希算法的学生画像个性化推荐系统的设计与实现

Design and implementation of student portrait personalized recommendation system based on deep hash algorithm

为了提升学生画像个性化推荐的效果,研究设计了一种基于深度哈希算法的学生画像个性化推荐系统。通过使用深度哈希算法结合经过处理的学生信息,进行了学生信息特征标签的提取,并构建了学生画像标签维度模型,从而提升了学生画像的生动性。根据学生画像标注的学生特征,在学校课程资源特征数据集中进行搜索匹配,并根据排序后的检索结果生成推荐结果。实验结果表明,该系统能够有效地采集和预处理学生信息,并成功构建学生画像,完成学生画像的个性化推荐。

In order to improve the effectiveness of personalized recommendation for student profiles,a personalized recommendation system for student profiles based on deep hash algorithm is designed in this study.By combining deep hash algorithm with processed student information,feature labels of student information are extracted,and a dimension model of student portrait labels is constructed,thereby improving the vividness of student portraits.Based on the student characteristics annotated by student portraits,searches and matches are conducted in the school curriculum resource feature dataset,and recommendation results are generated based on the sorted search results.The experimental results show that the system is capable of effectively collecting and preprocessing student information,successfully constructing student profiles and delivering personalized student profile recommendations.