e-LION: Data integration semantic model to enhance predictive analytics in e-Learning

作者：

Highlights：

• e-LION semantic approach is proposed for e-learning data source integration.

• An OWL Ontology is designed for e-learning, including SWRL reasoning rules.

• The proposal is validated with four real-world (Moodle) and academic cases study.

• Obtained semantised data successfully feed predictive machine learning models.

• We provide actual e-learning users with a model to enhance their analytics.

摘要

•e-LION semantic approach is proposed for e-learning data source integration.•An OWL Ontology is designed for e-learning, including SWRL reasoning rules.•The proposal is validated with four real-world (Moodle) and academic cases study.•Obtained semantised data successfully feed predictive machine learning models.•We provide actual e-learning users with a model to enhance their analytics.

论文关键词：E-learning,Ontology,Open data,Data analysis,Knowledge graph

论文评审过程：Received 16 November 2021, Revised 16 September 2022, Accepted 20 September 2022, Available online 27 September 2022, Version of Record 7 October 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118892