基于协同过滤算法的英语视听资源个性化推荐技术  

Personalized Recommendation Technology of English Audio-Visual Resources Based on Collaborative Filtering Algorithm

作　　者：李琼 宋小林[2] LI Qiong;SONG Xiaolin(Xuancheng Vocational and Technical College,Xuancheng,Anhui 242000,China;Jining Normal University,Ulanqab,Inner Mongolia 012000,China)

机构地区：[1]宣城职业技术学院,安徽宣城242000 [2]集宁师范学院,内蒙古乌兰察布012000

出　　处：《保定学院学报》2024年第5期112-116,共5页Journal of Baoding University

基　　金：安徽省高校人文社科研究重点项目“基于AI技术的高水平ESP教学全生态模式构建研究”(2022AH052774);安徽省职业与成人教育学会课题“‘双高’建设背景下的高质量ESP教学生态模式构建研究”(AZCJ2023255);宣城职业技术学院院级质量工程项目“基于CSE模式的高等学历继续教育教学质量评价体系创新发展研究”(2023gdjxjy01)。

摘　　要：对英语视听资源进行深度语义分析,提取资源关键特征;分析英语视听资源用户的学习偏好特征,将其与视听资源语义特征匹配;利用卷积神经网络深度融合学习偏好,构建英语视听资源个性化推荐模型;引入免疫进化算法优化协同过滤算法,求解推荐模型,实现英语视听资源个性化推荐.测试结果表明该方法的推荐命中率和推荐准确率均在90%以上,召回率始终稳定在87.11%以上,具有较好的个性化推荐效果.Conduct deep semantic analysis of English audio-visual resources,extract the key features of resources;analyze the learning preference characteristics of English audio-visual resources,match their semantic features;use convolutional neural network to deeply integrate learning preferences,build the personalized recommendation model of English audio-visual resources;introduce the immune evolution algorithm to optimize the collaborative filtering algorithm,solve the recommendation model,and realize the personalized recommendation of English audio-visual resources.The test results show that the recommendation hit rate and recommendation accuracy of this method are above 90%,and the recall rate is always stable above 87.11%,which has good personalized recommendation effect.

关 键 词：协同过滤算法 英语视听资源 个性化推荐 资源关键特征 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]