SWA-KMDLS: An enhanced e-Learning Management System using Semantic Web and Knowledge Management technology

Ahmad Mukhlason, A. Mahmood, N. Arshad, A. Z. Abidin
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Abstract

In knowledge economy age in which knowledge have become the most precious resource, e-Learning is used to not only acquire knowledge but also to maintain competitiveness and advantages for individuals or organizations. However, the early promise of e-Learning has not been fully realized. In most of its implementation, it is not more than a handout being published online. This paper aims to exploit the Semantic Web (SW), Knowledge Management (KM) technology two emerging and promising technology to enhance the existing e-Learning Management System (LMS). An Ontology approach that is the backbone of SW and KM is introduced for developing (semi-) automatic ontological knowledge base construction system (SAOKBCS) and automated question answering system (Aquas) in the proposed e-Learning system. The experiment conducted has shown that the SAOKBCS can extract concept that is the main component of Ontology from text learning object with precision of 86.67%, thus saving the expert time and effort to build Ontology manually. Additionally the experiment on Aquas has shown that more than 80% of users are satisfied with answers provided by the system. The expert locator framework can also improve the performance of Aquas in the future use.
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基于语义网和知识管理技术的增强型电子学习管理系统
在知识经济时代,知识已成为最宝贵的资源,e-Learning不仅是获取知识的手段,也是个人或组织保持竞争力和优势的手段。然而,电子学习的早期承诺尚未得到充分实现。在大多数实施过程中,它只不过是一份在线发布的讲义。本文旨在利用语义网(SW)、知识管理(KM)技术这两种新兴且有发展前景的技术来增强现有的电子学习管理系统(LMS)。在提出的电子学习系统中,引入了作为软件和知识管理主干的本体方法来开发(半)自动化本体知识库构建系统(SAOKBCS)和自动问答系统(Aquas)。实验结果表明,SAOKBCS能够以86.67%的准确率从文本学习对象中提取本体的主要组成部分概念,从而节省了专家手工构建本体的时间和精力。此外,在Aquas上的实验表明,超过80%的用户对系统提供的答案感到满意。专家定位框架还可以在未来的使用中提高Aquas的性能。
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