@inproceedings{canal-esteve-gutierrez-2024-educational,
title = "Educational Material to Knowledge Graph Conversion: A Methodology to Enhance Digital Education",
author = "Canal-Esteve, Miquel and
Gutierrez, Yoan",
editor = "Biswas, Russa and
Kaffee, Lucie-Aim{\'e}e and
Agarwal, Oshin and
Minervini, Pasquale and
Singh, Sameer and
de Melo, Gerard",
booktitle = "Proceedings of the 1st Workshop on Knowledge Graphs and Large Language Models (KaLLM 2024)",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.kallm-1.9",
pages = "85--91",
abstract = "This article argues that digital educational content should be structured as knowledge graphs (KGs). Unlike traditional repositories such as Moodle, a KG offers a more flexible representation of the relationships between concepts, facilitating intuitive navigation and discovery of connections. In addition, it integrates effectively with Large Language Models, enhancing personalized explanations, answers, and recommendations. This article studies different proposals based on semantics and knowledge modelling to determine the most appropriate ways to strengthen intelligent educational technologies.",
}
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<abstract>This article argues that digital educational content should be structured as knowledge graphs (KGs). Unlike traditional repositories such as Moodle, a KG offers a more flexible representation of the relationships between concepts, facilitating intuitive navigation and discovery of connections. In addition, it integrates effectively with Large Language Models, enhancing personalized explanations, answers, and recommendations. This article studies different proposals based on semantics and knowledge modelling to determine the most appropriate ways to strengthen intelligent educational technologies.</abstract>
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%0 Conference Proceedings
%T Educational Material to Knowledge Graph Conversion: A Methodology to Enhance Digital Education
%A Canal-Esteve, Miquel
%A Gutierrez, Yoan
%Y Biswas, Russa
%Y Kaffee, Lucie-Aimée
%Y Agarwal, Oshin
%Y Minervini, Pasquale
%Y Singh, Sameer
%Y de Melo, Gerard
%S Proceedings of the 1st Workshop on Knowledge Graphs and Large Language Models (KaLLM 2024)
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F canal-esteve-gutierrez-2024-educational
%X This article argues that digital educational content should be structured as knowledge graphs (KGs). Unlike traditional repositories such as Moodle, a KG offers a more flexible representation of the relationships between concepts, facilitating intuitive navigation and discovery of connections. In addition, it integrates effectively with Large Language Models, enhancing personalized explanations, answers, and recommendations. This article studies different proposals based on semantics and knowledge modelling to determine the most appropriate ways to strengthen intelligent educational technologies.
%U https://aclanthology.org/2024.kallm-1.9
%P 85-91
Markdown (Informal)
[Educational Material to Knowledge Graph Conversion: A Methodology to Enhance Digital Education](https://aclanthology.org/2024.kallm-1.9) (Canal-Esteve & Gutierrez, KaLLM-WS 2024)
ACL