基于社区驱动与Web数据挖掘的个性化e-learning解决方案推荐系统研究

发布时间：2018-04-19 12:00

本文选题：终身学习 + 数字化学习　；参考：《东北师范大学》2009年硕士论文

【摘要】： 建设终身学习体系是当前我国教育发展的重要内容,本文从终身学习环境下的e-learning平台建设为出发点,整合Web数据挖掘理论和社区驱动理论,构建了一种个性化e-learning解决方案推荐系统(PELSRS),该系统能够兼容不同的学习情境,以个性化自主性学习为主要学习方式,利用社区驱动来实现资源和信息的构建,并充分利用网络智能来实现个性化推荐。论文围绕PELSRS的理论和技术实现进行了全面的探讨。论文首先对PELSRS的相关理论进行了研究,提出了个性化e-learning解决方案的概念模型,并对其个性化策略进行了探讨;然后对社区驱动在PELSRS中的应用进行了研究,提出了多项整合的策略,并对系统中社会化动机维持机制进行了探讨;接下来论文使用Web数据挖掘对e-learning解决方案进行挖掘和推荐,设计了一种基于关联规则挖掘的e-learning解决方案推荐过程和推荐引擎;论文最后给出了系统的功能模型、主要数据库设计和用户交互界面图示,并对未来的研究工作和发展趋势进行了展望。
[Abstract]:The construction of life-long learning system is an important content of the development of education in China. This paper integrates the theory of Web data mining and community-driven theory from the construction of e-learning platform under the life-long learning environment.In this paper, a personalized e-learning solution recommendation system (PELSRSX) is constructed. The system can be compatible with different learning situations, take individualized autonomous learning as the main learning method, and realize the construction of resources and information by community-driven.And make full use of network intelligence to realize personalized recommendation.This paper discusses the theory and technology of PELSRS.Firstly, this paper studies the relevant theories of PELSRS, puts forward the conceptual model of personalized e-learning solution, and discusses its individuation strategy, and then studies the application of community driven in PELSRS.Several integrated strategies are put forward, and the maintenance mechanism of social motivation in the system is discussed. Secondly, Web data mining is used to mine and recommend the e-learning solution.A e-learning solution recommendation process and recommendation engine based on association rule mining is designed. Finally, the function model of the system, the main database design and user interface diagram are given.The future research work and development trend are prospected.
【学位授予单位】：东北师范大学
【学位级别】：硕士
【学位授予年份】：2009
【分类号】：TP311.13;G434

【引证文献】