基于协同过滤推荐算法的第二课堂学习系统架构

Research of Second Class Learning System Structure Based on Collaborative Filtering Recommendation Algorithm

随着互联网技术的飞速演化,网络学习资源愈加纷繁复杂。在计算机网络及IT领域,软件工程专业的编程语言、软件开发框架等软件开发技术日新月异,这对学习者及时了解和掌握新的知识,特别是高等学校学生选择合适的学习资料并接受答疑带来了很大的挑战,因此构建一个辅助学生课外学习的第二课堂学习系统具有重要意义。第二课堂学习系统的App端方便用户随时随地学习技术文章。自媒体端为用户提供文章发布功能。管理端提供爬虫系统和推荐系统的管理,其中爬虫系统能够丰富文章库,方便用户检索和推荐系统进行文章数据分析;推荐系统利用Word2Vec模型和TextRank模型进行相似文章的推荐,采用协同过滤算法进行文章的召回以及逻辑回归模型和Wide&Deep排序模型进行文章的推荐。

With the rapid evolution of Internet technology,online learning resources are becoming more and more complex.The software development technologies such as programming language and software development framework of software engineering major are changing with each passing day,which brings great challenges for students to choose appropriate learning materials and get timely answers.Therefore,it is of great significance to build a second class learning system to assist students'extracurricular learning.The App end of the second class learning system is convenient for users to learn technical articles anytime and anywhere.The we media side provides users with the function of publishing articles.The management side provides the management of crawler system and recommendation system.The crawler system can enrich the article database and facilitate users to retrieve and analyze the article data in the recommendation system;The recommendation system uses Word2Vec model and TextRank model to recommend similar articles,uses collaborative filtering algorithm to recall articles,and uses logistic regression model and Wide&Deep model to recommend articles.