Ontology Construction Methods for the Tourism Domain Oriented to the Semantic Web

Shengyu Gu; Mu Zhang

doi:10.63313/CS.8021

Authors

Shengyu Gu School of Geography and Tourism, Huizhou University, Huizhou 516007, Guangdong, China Author
Mu Zhang Shenzhen Tourism College, Jinan University, Shenzhen 518053, Guangdong, China Author

DOI:

https://doi.org/10.63313/CS.8021

Keywords:

Semantic Web, Tourism Ontology, Ontology Construction, Knowledge Graph, Ontology Learning, Large Language Models

Abstract

With the accelerating transformation of the tourism industry toward intelligent services, achieving semantic integration and efficient organization of heterogeneous tourism data has become a critical issue. Semantic Web technologies provide a solid foundation for ontology construction in the tourism domain, enabling the development of structured and machine-interpretable knowledge systems. This paper presents a comprehensive review of tourism ontology construction methods, covering key concepts, ontology types, and construction workflows. It further analyzes both manual and (semi-)automated approaches, compares mainstream ontology engineering tools, and summarizes representative case studies. The study highlights major challenges such as data heterogeneity, ontology consistency, and cross-cultural adaptability. Finally, the paper explores future directions including ontology learning, integration with knowledge graphs, large language model-assisted construction, and the application of graph neural networks. The findings aim to support researchers and practitioners in designing more adaptive, scalable, and intelligent semantic frameworks for tourism information systems.

References

[1] Lee, T. B., Hendler, J., & Lassila, O. (2001). The semantic web. Scientific american, 284(5), 34-43.

[2] Gruber, T. R. (1993). A translation approach to portable ontology specifications. Knowledge acquisition, 5(2), 199-220.

[3] Antoniou, G., & Van Harmelen, F. (2004). A semantic web primer. MIT press.

[4] Gómez-Pérez, A., Fernández-López, M., & Corcho, O. (2004). Ontological Engineering: with examples from the areas of Knowledge Management, e-Commerce and the Semantic Web. London: Springer London.

[5] Maedche, A., & Staab, S. (2005). Ontology learning for the semantic web. IEEE Intelligent systems, 16(2), 72-79.

[6] Al-Aswadi, F. N., Chan, H. Y., & Gan, K. H. (2020). Automatic ontology construction from text: a review from shallow to deep learning trend. Artificial Intelligence Review, 53(6), 3901-3928.

[7] Wache, H., Voegele, T., Visser, U., Stuckenschmidt, H., Schuster, G., Neumann, H., & Hübner, S. (2001, August). Ontology-based integration of information-a survey of existing approaches. In Ois@ ijcai.

[8] Garcia, R., & Celma, O. (2005, November). Semantic Integration and Retrieval of Multimedia Metadata. In Se-mAnnot@ ISWC.

[9] Fensel, D., Van Harmelen, F., Horrocks, I., McGuinness, D. L., & Patel-Schneider, P. F. (2005). OIL: An ontology infrastructure for the semantic web. IEEE intelligent systems, 16(2), 38-45.

[10] Flouris, G., Manakanatas, D., Kondylakis, H., Plexousakis, D., & Antoniou, G. (2008). Ontology change: classifi-cation and survey. The Knowledge Engineering Review, 23(2), 117-152.

[11] Buitelaar, P., Cimiano, P., & Magnini, B. (Eds.). (2005). Ontology learning from text: methods, evaluation and ap-plications (Vol. 123). IOS press.

[12] Funk, M., Hosemann, S., Jung, J. C., & Lutz, C. (2023). Towards ontology construction with language models. arXiv preprint arXiv:2309.09898.