Comparative Study of Knowledge Graph Models in Education Domain

Zineb Elkaimbillah, Maryem Rhanoui, Mounia Mikram, Bouchra El Asri

2021

Abstract

Knowledge graph (KG) technologies are improving Artificial Intelligence. It can effectively expand the breadth of search results. Therefore, KGs continue to solve several problems in different domains, including the education field. The application of educational KGs to learning systems has recently been expanded due to increased demand in the education sector and the importance of KGs application to learning systems. In this article, we present the knowledge Graph approach, the methodology of KG development, and analyze each step. Also, we discuss the popular KG Embedding models. We provide a comparative study of KG models in the education field.

Paper Citation

in Harvard Style

Elkaimbillah Z., Rhanoui M., Mikram M. and El Asri B. (2021). Comparative Study of Knowledge Graph Models in Education Domain. In Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - Volume 1: BML, ISBN 978-989-758-559-3, pages 339-344. DOI: 10.5220/0010733800003101

in Bibtex Style

@conference{bml21,
author={Zineb Elkaimbillah and Maryem Rhanoui and Mounia Mikram and Bouchra El Asri},
title={Comparative Study of Knowledge Graph Models in Education Domain},
booktitle={Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - Volume 1: BML,},
year={2021},
pages={339-344},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010733800003101},
isbn={978-989-758-559-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - Volume 1: BML,
TI - Comparative Study of Knowledge Graph Models in Education Domain
SN - 978-989-758-559-3
AU - Elkaimbillah Z.
AU - Rhanoui M.
AU - Mikram M.
AU - El Asri B.
PY - 2021
SP - 339
EP - 344
DO - 10.5220/0010733800003101