Abstract
The lack of knowledge about food ingredients can be risky and lead to serious complications for those with chronic diseases and food allergies. This paper proposes ontology-based Food Safety Counseling System (FSCS) that help the users with chronic diseases and food allergies to select their food. FSCS’ aim to investigate the level of appropriate food products chosen by the users. The proposed models aim is to measure semantic relations between effected elements (The Main Item) of food product and the personal health status of users to provide professional advice about risky ingredient through six level of risk factor. It contains the Egypt food safety ontology (EFSO) and set of rules created based on knowledge elicited from experts in food safety domain to discover the tacit knowledge and allow semantic integration by applying forward-chaining deduction method and inference mechanism to knowledge base. The results indicate the model works effectively with high accuracy.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Egyptian Food Safety Authority (2017) The EFSA register. http://www.nfsa.gov.eg. Accessed 10 Oct 2017
Gruber, T.R.: A translation approach to portable ontology specifications. Knowl. Acquisition 5(2), 199–220 (1993)
Kawtrakul, A., Pechsiri, C.: Ontology driven k-Portal construction and K-service provision. In: Paper Presented at the Fifth International Conference on Language Resources and Evaluation, Italy, 24–26 May 2006 (2006)
Chuang, H., Ko, W.-M.: Automated food ontology construction mechanism for diabetes diet care. In: Paper Presented at the Sixth International Conference on Machine Learning and Cybernetics, Hong Kong, 19–22 August 2007 (2007)
Yang, Y., Junping, D., Hu, J.: Study on food safety ontology reasoning application based on Jena. In: Paper Presented at the International Conference on Communication and Technology Applications, China, 14–16 Oct 2011 (2011)
He, B., Yang, Y.: Semantic query expansion method for food safety domain. In: Paper Presented at IEEE International Conference on Computer Science and Automation Engineering, China, 22–24 June 2012 (2012)
Wijosika, A., Srivihok, A.: Thai food safety document searching system by ontology. In: Paper Presented at the 2nd International Conference on Research in Science, Engineering and Technology, Dubai, 21–22 March 2014 (2014)
Çelik, D.: FoodWiki: ontology-driven mobile safe food consumption system. Sci. World J. (2015). https://doi.org/10.1155/2015/475410
Jaro, M.A.: Advances in record-linkage methodology as applied to matching the 1985 census of Tampa, Florida. J. Am. Stat. Assoc. 84(406), 414–420 (1989). https://doi.org/10.1080/01621459.1989.10478785
International Article Number. http://www.barcodeisland.com/ean13.phtml. Accessed 12 Feb 2018
Angel, M.: Knowledge acquisition Techniques (2011). http://www.epistemics.co.uk/No-te/174-0-0.htm. Accessed 15 Mar 2018
Öhgren, A., Sandkuhl, K.: Toward a methodology for ontology development in small and medium-sized enterprises. In: Paper presented at the International Conference on Applied Computing, Portugal, 22–25 February 2005 (2005)
Gon, R., et al.: Protégé platform (2017). https://protege.stanford.edu/. Accessed 15 Des 2017
Horrocks, I., et al.: SWRL: a semantic web rule language combining OWL and rule MI (2004). https://www.w3.org/Submission/SWRL/. Accessed 10 Oct 2017
Sattler, U.: Description Logic Reasoner (2015). http://www.cs.man.ac.uk/~sattler/resoners.-html. Accessed 10 Oct 2017
Sirin, E., Parsia, B.: Pellet: a practical OWL-DL reasoner. J. Web Seman. 51–53 (2005). https://doi.org/10.1016/j.websem.2007.03.004
Glimm, B., Horrocks, I.: HermiT: an OWL 2 reasoner. J. Autom. Reasoning Manuscript 53, 245–269 (2014). https://doi.org/10.1007/s10817-014-9305-1
Joshi, M., Meech, A., et al.: Business Rule Using OWL and SWRL. In: Advances in Semantic Computing (2010)
Al-Ajlan, A.: The comparison between forward and backward chaining. Int. J. Mach. Learn. Comput. https://doi.org/10.7763/ijmlc.2015.v5.492
Egyptian Ministry of Agriculture Egypt (2018) The EMAE register. http://far-malr.gov.eg. Accessed 20 May 2018
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Ragab, Y.A., Elfakhrany, E.F., Sharoba, A.M. (2020). Ontology-Based Food Safety Counseling System. In: Hassanien, A., Shaalan, K., Tolba, M. (eds) Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2019. AISI 2019. Advances in Intelligent Systems and Computing, vol 1058. Springer, Cham. https://doi.org/10.1007/978-3-030-31129-2_56
Download citation
DOI: https://doi.org/10.1007/978-3-030-31129-2_56
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-31128-5
Online ISBN: 978-3-030-31129-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)