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SWA-KMDLS: An Enhanced e-Learning Management System Using Semantic Web and Knowledge Management Technology

机译:SWA-KMDLS:使用语义网络和知识管理技术的增强型电子学习管理系统

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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.
机译:在知识经济时代,知识已成为最宝贵的资源,电子学习不仅可以获得知识,而且习惯于维持个人或组织的竞争力和优势。但是,电子学习的早期承诺尚未完全实现。在其大部分实施中,它不仅仅是在线发布的讲义。本文旨在利用语义网络(SW),知识管理(KM)技术两种新兴和有希望的技术,以增强现有的电子学习管理系统(LMS)。作为SW和KM骨干的本体方法,用于在所提出的电子学习系统中开发(半)自动本体知识库施工系统(SAOKBC)和自动问题应答系统(AQUAS)。进行的实验表明,索奥布斯可以提取来自文本学习对象的本体论的主要成分,精度为86.67%,从而节省了手动构建本体的专家时间和精力。此外,Aquas的实验表明,超过80%的用户对系统提供的答案感到满意。专家定位器框架还可以提高未来使用的性能。

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