文章基本信息

标题：A Personalized E-Learning Recommender System Using the Concept of Fuzzy Tree Matching
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作者：G. Poorni ; K. Balaji ; C. DeepthiNivetha 等
期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2015
卷号：4
期号：11
页码：4039-4043
出版社：Shri Pannalal Research Institute of Technolgy
摘要：The rapid development of e-learning systems provides learners with large opportunities to access learning activities through online. This greatly supports and enhances learning practices of users. However the issues related to e-learning systems reduces the success of its application. This is because of many learning activities such as various learning materials, subjects, and learning resources that are emerging in this online world which makes an e- learning system difficult. The individual learners find it difficult to select optimized activities for their particular situations/requirements/query, because there is no personalized service belonging to that particular user. Recommender systems that aim in providing personalized environment for studying materials can be used to solve those issues in e- learning system. However, e-learning systems need to be able to handle certain special requirements or issues. They are 1) learning activities and learners' profiles that are often presented in tree structures; 2) learning activities contain more uncertain categories which additionally contain unclear and uncertain data 3) there are pedagogical issues, such as the precedence order for a particular user cannot be given separately for each user. To deal with these three requirements, this survey proposes two techniques called a fuzzy tree-structured learning activity model and a learner profile model. These two methods comprehensively explain the difficult learning activities and learner profiles. In these two models, fuzzy category trees and related preference orders are presented to know the semantic relations between learning activities or learner requirements of each individual learner.
关键词：E-learning; fuzzy sets; knowledge- ; based recommendation; recommender systems; tree ; matching.