【作者】 李娜；

【导师】 谭长庚；

【作者基本信息】 中南大学 ， 软件工程， 2013， 硕士

【摘要】 随着高校的学生选修课程应用于互联网选修,互联网逐渐成为学生获取信息的主要途径。如何从众多选修课程中,快速搜索与本人兴趣一致的选修课程,是推荐系统应用的重要研究方向。基于网络平台查询课程信息,学生提取有价值的课程信息比较困难,大多数学生选修课程比较盲目,使某些课程因排序或学生自身了解程度不够的情况下变为无人选修课程。目前,高校选修课程的推荐系统多数存在无推荐功能、推荐质量差、响应时间较长、智能推荐度较低等情况,不能满足学生兴趣与智能的需要。而利用学生对选修课程的评价、学生个体的兴趣智能等特点建立的推荐系统能够有效地解决这些问题。本文首先介绍高校选修课程的现状与高校选修课程的培养目标,确定高校选修课程应建立以职业规划与工作过程的培养目标,强调以职业岗位所需的实际能力来开设选修课程,将选修课程知识与具体职业实践相对应。了解高校生的兴趣特点与智能倾向,分析高校学生的兴趣特点与选修课程的特征,获取相似性特征来完成课程的推荐。阐述了基于内容的高校课程推荐方法、协同过滤推荐方法。文章总结高校课程的内容推荐方法和学生之间对高校课程评价协同过滤的推荐方法的优缺点,根据学生兴趣特征与选修课程特征设计推荐系统的核心算法,采用两种推荐技术相结合的混合推荐方法。根据高校选修课程推荐系统的效能评价指标体系,分析评估指标,建立两种评价指标对选修课程基于内容过滤进行评价。然后对选修课程推荐系统的设计原则进行分析,结合高校课程推荐系统的相关业务功能,设计课程推荐系统的整体架构图,根据系统功能需求完成基于混合协同过滤的选课推荐系统设计。系统基于J2EE架构技术和B/S三层体系模式设计,论文详细阐述选课系统登录模块、选修课课程申报模块、选修课程开课通知模块、学生选课推荐模块等功能的实现。选修课程的混合协同推荐系统它能够提供个性化推荐、精品课程推荐、选修热门推荐等多方面的推荐。论文实现基于混合协同过滤的高校选修课推荐系统的设计,验证推荐系统的核心算法,系统具有较好的推荐功能。更多还原

【Abstract】 With the vocational college students to take elective courses applied to the Internet, the Internet has become the main way student’s access to information. How elective courses, quick search and I interested in the same elective courses, is an important research direction recommended system applications. Web-based platform details of the curriculum information, student extract valuable course information more difficult, most student’s elective courses are blind, so that some sort or the student’s own curriculum because of insufficient understanding of the case becomes no elective courses. Currently, elective courses in vocational colleges majority recommendation system exists no recommendation function, it is recommended poor quality, response time is longer, intelligent recommendation is low, etc., can not meet the needs of students interested and intelligent. The use of student evaluation of elective courses, students interested in intelligence and other characteristics of individuals to establish a recommendation system can effectively solve these problems.This paper describes the status of vocational elective courses and elective courses in vocational training objectives, to determine vocational elective courses should be established to career planning and job training objectives process, emphasizing the practical ability required for professional positions to open elective courses that will elective courses with specific knowledge corresponding professional practice. Interest in vocational students understand the features and intelligence tend to analyze characteristics of vocational students’ interests and characteristics of elective courses to obtain similar features to complete the course is recommended. Describes the content-based vocational courses recommended method, collaborative filtering recommendation. Article summarizes the content of vocational courses recommended methods and students on vocational curriculum evaluation method for collaborative filtering recommendation advantages and disadvantages of student interest and elective courses feature design characteristics recommendation system core algorithm using two recommended techniques recommended method for mixing. Vocational elective courses recommendation system based on performance evaluation index system for Exploration, analysis and evaluation indicators, evaluation index create two elective courses based on content filtering evaluation. Then elective courses recommended system design principles for analysis, recommendation systems combine vocational courses related business functions, the overall design course recommendation system architecture diagram, according to the system functional requirements to achieve the course based on hybrid collaborative filtering recommendation system design. The system is based on J2EE technology and B/S three-tier architecture model design, the article details the elective system login module, reporting module elective courses, elective courses start notification module, student elective recommended modules, etc. functions are implemented. Elective courses Hybrid Synergy recommendation system is its ability to provide personalized recommendation, excellent course recommended, recommended, and many other popular elective recommended.This hybrid-based collaborative filtering recommendation vocational elective system design, verification recommendation system core algorithm, the system has a good recommendation function.更多还原