A Personalized Course Recommender System for E-Learning

IF 1 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS International Journal of Communication Networks and Distributed Systems Pub Date : 2019-06-05 DOI:10.30534/ijns/2019/03832019
Athira S Nath
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引用次数: 1

Abstract

In recent years, the internet has witnessed an aggressive growth in the amount of learning resources. This explosion of learning resources on the internet results in expanded interest for online learning resources by learners in e-learning environment. With this expansion of online learning resources, learners are experiencing challenges in deciding learning resources that are valuable and significant to their learning needs. Recommender systems can overcome this issue by filtering out inappropriate learning resources and automatically recommending suitable resources to the learners according to their interests. In this paper we are focusing on a course recommender system in an e-learning platform which tries to intelligently recommend courses to the learners based on their interest. This recommendation approach is used to provide learners some suggestions when they have trouble in choosing correct courses. It also allows us to study the behavior of learner regarding their course selection and suggests the best combination of courses in which the learners are interested
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面向网络学习的个性化课程推荐系统
近年来,互联网见证了学习资源数量的迅猛增长。互联网上学习资源的爆炸式增长导致了在线学习环境下学习者对在线学习资源的兴趣扩大。随着在线学习资源的扩展,学习者在选择对他们的学习需求有价值和重要的学习资源方面面临着挑战。推荐系统可以通过过滤掉不合适的学习资源,并根据学习者的兴趣自动推荐合适的资源来克服这个问题。本文主要研究了一个基于网络学习平台的课程推荐系统,该系统可以根据学习者的兴趣向学习者智能推荐课程。当学习者在选择正确的课程时遇到困难时,这种推荐方法可以为学习者提供一些建议。它还允许我们研究学习者在选课方面的行为,并建议学习者感兴趣的课程的最佳组合
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来源期刊
CiteScore
2.50
自引率
46.20%
发文量
57
期刊介绍: IJCNDS aims to improve the state-of-the-art of worldwide research in communication networks and distributed systems and to address the various methodologies, tools, techniques, algorithms and results. It is not limited to networking issues in telecommunications; network problems in other application domains such as biological networks, social networks, and chemical networks will also be considered. This feature helps in promoting interdisciplinary research in these areas.
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