期刊
出版社
IEEE
DOI: 10.1109/iceiec.2019.8784572
关键词
knowledge graph; educational resource; MOOC-KG; knowledge modeling; entity extraction; knowledge fusion
The exponential growth of Massive Open Online Courses (MOOCs) provides increasing learning options along with distinguishing difficulties in choosing courses or finding learning paths for learners. To improve online learning resource utilization, a knowledge graph, MOOC-KG, collecting and formulating the information of online courses on major platforms was constructed. The aim of MOOC-KG is to not only provide users with a new MOOC resource organization but also supply an easy approach for learning resource using among several platforms. In our work, an acknowledged educational ontology was adopted to model the knowledge of online learning resources and the web information extraction methods were developed to collect the metadata on major platforms. The entity disambiguation and conflict resolution methods were adopted to integrate the resources among different platforms. As a result, MOOC-KG is the biggest MOOC-related knowledge graph, which represents and stores 28591 instances with their corresponding relations, including 4 platforms, 604 universities, 18671 teachers and 9312 courses until now. Related valuable data analyses illustrate the fundamental information and reveal explorable parts of MOOC-KG. We have released the related project on GitHub to facilitates further improvement and extensive use.
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