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Graph-based semantic annotation for enriching educational content with linked data
DOI:10.1016/j.knosys.2013.10.007.png)
摘要
En 中文
In this paper, a new approach to semantic annotation with linked data in the field of document enrichment is presented. This application has been developed in the domain of Education and contrary to traditional semantic annotation, which relates each relevant term of the document with an instance of the ontology, in our approach relevant terms are connected to a (sub)graph of the ontology. Specifically, each relevant term is related to an instance which is expanded to a predefined depth limit, so the term is finally annotated with a (sub)graph. During the expansion process, instances unrelated with the document topics are ruled out, so only relevant and contextualized information is finally included. As result of this process, the document is annotated with a set of interconnected (sub)graphs, and students may access and navigate through these contents to deepen the topics described in the document. This approach has several benefits. From the document enrichment perspective, a set of (sub)graphs, provides a better description, moreover considering the semantic nature of linked data. From the computational perspective, this approach is also more suitable, particularly in the domain of Education. Filtering linked data is computationally expensive, and thus this process cannot be performed in real time. Our approach has been validated in the e-Learning domain and compared with similar approaches that also annotate with linked data. (C) 2013 Elsevier B.V. All rights reserved.
Keyword:
Semantic annotation
Linked data
Semantic web
Ontologies
Technology enhanced learning
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
K
IF:
7.6
论文数:
1.3W
被引数:
4.5W

