Building Intelligent Semantic Educational System (ISES) Based on Ontology and Semantic Web Mining

A. Amin
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引用次数: 3

Abstract

This research presents a method to build an intelligent semantic education system based on two novel techniques namely ontology and semantic web mining. Ontologies are a powerful mechanism to solve a retrieval problem that is exacerbated rapidly within the modern educational systems, when there are individual differences between instructors and learners in the previous backgrounds and levels of knowledge. In intelligent education systems, four types of ontology are identified that represent knowledge: students, content, education, and structure. There is a promising approach for satisfying the intelligent education systems requirements, which is one of the most prominent semantic Web ideas, based on commonly shared meaning (ontology) and metadata processed automatically. This approach can be supported using semantic querying and conceptual navigation for learning materials.One of the important results of this paper is the depth of most of the inferences derived from learning ontologies. Relations such as "has_Part" and "is_Part_Of" and their interplay can be easy dealing by the users. Therefore, this type of thinking can be presented through an automatic mechanism, and semantic information is necessary for reasoning about an automatic occurrence.
基于本体和语义Web挖掘的智能语义教育系统构建
本文提出了一种基于本体和语义web挖掘两种新技术构建智能语义教育系统的方法。本体论是一种强大的机制,可以解决在现代教育系统中,由于教师和学习者在以前的背景和知识水平上存在个体差异而迅速加剧的检索问题。在智能教育系统中,可以识别四种表示知识的本体:学生、内容、教育和结构。基于共同共享的意义(本体)和自动处理的元数据,是满足智能教育系统需求的一种很有前途的方法,是语义Web思想中最突出的思想之一。这种方法可以使用学习材料的语义查询和概念导航来支持。本文的一个重要结果是大多数从学习本体中得出的推论的深度。诸如“has_Part”和“is_Part_Of”之类的关系及其相互作用可以很容易地被用户处理。因此,这种类型的思维可以通过一种自动机制来呈现,语义信息对于自动发生的推理是必要的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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