ODKAR: “Ontology-Based Dynamic Knowledge Acquisition and Automated Reasoning Using NLP, OWL, and SWRL”

Claire Ponciano, Markus Schaffert, Jean-Jacques Ponciano

2024

Abstract

This paper introduces a novel approach to dynamic ontology creation, leveraging Natural Language Processing (NLP) to automatically generate ontologies from textual descriptions and transform them into OWL (Web Ontology Language) and SWRL (Semantic Web Rule Language) formats. Unlike traditional manual ontology engineering, our system automates the extraction of structured knowledge from text, facilitating the development of complex ontological models in domains such as fitness and nutrition. The system supports automated reasoning, ensuring logical consistency and the inference of new facts based on rules. We evaluate the performance of our approach by comparing the ontologies generated from text with those created by a Semantic Web technologies expert and by ChatGPT. In a case study focused on personalized fitness planning, the system effectively models intricate relationships between exercise routines, nutritional requirements, and progression principles such as overload and time under tension. Results demonstrate that the proposed approach generates competitive, logically sound ontologies that capture complex constraints.

Paper Citation

in Harvard Style

Ponciano C., Schaffert M. and Ponciano J. (2024). ODKAR: “Ontology-Based Dynamic Knowledge Acquisition and Automated Reasoning Using NLP, OWL, and SWRL”. In Proceedings of the 20th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST; ISBN 978-989-758-718-4, SciTePress, pages 457-465. DOI: 10.5220/0013071500003825

in Bibtex Style

@conference{webist24,
author={Claire Ponciano and Markus Schaffert and Jean-Jacques Ponciano},
title={ODKAR: “Ontology-Based Dynamic Knowledge Acquisition and Automated Reasoning Using NLP, OWL, and SWRL”},
booktitle={Proceedings of the 20th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST},
year={2024},
pages={457-465},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013071500003825},
isbn={978-989-758-718-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST
TI - ODKAR: “Ontology-Based Dynamic Knowledge Acquisition and Automated Reasoning Using NLP, OWL, and SWRL”
SN - 978-989-758-718-4
AU - Ponciano C.
AU - Schaffert M.
AU - Ponciano J.
PY - 2024
SP - 457
EP - 465
DO - 10.5220/0013071500003825
PB - SciTePress