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Effective e-learning recommendation system based on self-organizing maps and association mining

机译：基于自组织图和关联挖掘的有效的电子学习推荐系统

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Purpose - The purpose of this study is to propose a hybrid system to combine the self-organizing map (SOM) of a neural network with the data-mining (DM) method for course recommendation of the e-learning system.rnDesign/methodology/approach - This research constructs a hybrid system with artificial neural network (ANN) and data-mining (DM) techniques. First, ANN is used to classify the e-Learner types. Based on these e-Learner groups, users can obtain course recommendation from the group's opinions. When groups of related interests have been established, the DM will be used to elicit the rules of the best learning path. It is ideal for this system to stimulate learners' motivation and interest. Moreover, the hybrid approach can be used as a reference when learners are choosing between classes. Findings - In order to enhance the efficiency and capability of e-learning systems, the SOM method is combined to deal with cluster problems of DM systems, SOM/DM for short. It was found that the SOM/DM method has excellent performance.rnResearch limitations/implications - This research is limited by the fact that its participants are from a business college of a university in Taiwan, and it is applied by SOM/DM to recommend courses of e-learners. This research is useful in the domain of the e-learning system. Originality/value - The results of this research will provide useful information for educators to classify their e-learners or students more accurately, and to adapt their teaching strategies accordingly to retain valuable e-learners subject to limited resources. The experiments prove that it is ideal to stimulate learners' motivation and interest.
机译：目的-这项研究的目的是提出一个混合系统，将神经网络的自组织图（SOM）与数据挖掘（DM）方法相结合，以推荐电子学习系统的课程.rnDesign / methodology /方法-该研究构建了一个包含人工神经网络（ANN）和数据挖掘（DM）技术的混合系统。首先，使用ANN对电子学习器类型进行分类。基于这些电子学习者小组，用户可以从小组的意见中获得课程推荐。在建立了相关兴趣组之后，DM将被用于得出最佳学习路径的规则。该系统最理想的是激发学习者的动力和兴趣。此外，当学习者在课程之间进行选择时，混合方法可以用作参考。发现-为了提高电子学习系统的效率和功能，将SOM方法组合起来处理DM系统（简称SOM / DM）的集群问题。发现SOM / DM方法具有出色的性能。研究限制/意义-该研究受到参与者来自台湾一所大学的商学院的事实的限制，并且SOM / DM将其用于推荐课程电子学习器。这项研究在电子学习系统领域很有用。原创性/价值-这项研究的结果将为教育者提供有用的信息，以便他们更准确地对他们的电子学习者或学生进行分类，并相应地调整其教学策略，以保留有价值的电子学习者，但资源有限。实验证明，激发学习者的动力和兴趣是理想的。

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