Abstract
The wealth of information on nutrition and healthy diets along the web, as health web magazines or forums, often leads to confuse users in several ways. Reliability and completeness of information, as well as extracting only the relevant one becomes a critical issue, especially for certain groups of people such as the elderly. Likewise, heterogeneity of information representation and without a clear semantics hinders knowledge sharing and enrichment. In this paper, it is introduced a method to compute the semantic similarity between foods used in NutElCare, an ontology-based recommender system capable of collecting and representing relevant nutritional information from expert sources in order to providing adequate nutrition tips for the elderly. The knowledge base of NutElCare is an OWL ontology built from AGROVOC FAO thesaurus.
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References
Aberg, J.: Dealing with Malnutrition: A Meal Planning System for Elderly. In: AAAI Spring Symposium: Argumentation for Consumers of Healthcare, pp. 1–7 (2006)
OWL API, Java OWL API reference implementation, http://owlapi.sourceforge.net/
Benghazi, K., Hurtado, M.V., Hornos, M.J., Rodríguez, M.L., Rodríguez-Domínguez, C., Pelegrina, A.B., Rodríguez-Fórtiz, M.J.: Enabling correct design and formal analysis of Ambient Assisted Living systems. Journal of Systems and Software 85(3), 498–510 (2012)
Bermudez, M., Noguera, M., Hurtado-Torres, N., Hurtado, M.V., Garrido, J.L.: Analyzing a firm’s international portfolio of technological knowledge: A declarative ontology-based OWL approach for patent documents. Advanced Engineering Informatics (2013)
Blanco-Fernández, Y., Pazos-Arias, J.J., Gil-Solla, A., Ramos-Cabrer, M., López-Nores, M., García-Duque, J., Fernández-Vilas, A., Díaz-Redondo, R.P.: Exploiting synergies between semantic reasoning and personalization strategies in intelligent recommender systems: A case study. Journal of Systems and Software 81(12), 2371–2385 (2008)
Cobos, C., Rodriguez, O., Rivera, J., Betancourt, J., Mendoza, M., León, E., Herrera-Viedma, E.: A hybrid system of pedagogical pattern recommendations based on singular value decomposition and variable data attributes. Information Processing & Management 49(3), 607–625 (2013)
FAO: Agrovoc linked open data, http://aims.fao.org/aos/agrovoc/
Farsani, H.K., Nematbakhsh, M.: A semantic recommendation procedure for electronic product catalog 3, 86–91 (2006)
Freyne, J., Berkovsky, S.: Intelligent food planning: personalized recipe recommendation. In: Proceedings of the 15th International Conference on Intelligent User Interfaces, IUI 2010, pp. 321–324. ACM (2010)
Garrido, J.L., Hurtado, M.V., Noguera, M., Zurita, J.M.: Using a CBR approach based on ontologies for recommendation and reuse of knowledge sharing in decision making. In: Eighth International Conference on Hybrid Intelligent Systems, HIS 2008, pp. 837–842. IEEE (2008)
Horrocks, I., Patel-Schneider, P.F., Boley, H., Tabet, S., Grosof, B., Dean, M.: SWRL: A Semantic Web Rule Language Combining OWL and RuleML, http://www.w3.org/Submission/SWRL/
Loizou, A., Dasmahapatra, S.: Recommender systems for the semantic web (2006)
Noguera, M., Hurtado, M.V., Rodríguez, M.L., Chung, L., Garrido, J.L.: Ontology-driven analysis of uml-based collaborative processes using owl-dl and cpn. Science of Computer Programming 75(8), 726–760 (2010)
Peis, E., del Castillo, J.M., Delgado-López, J.: Semantic recommender systems. analysis of the state of the topic. Hipertext. Net 6, 1–5 (2008)
PIPS: Personalised information platform for health and life services, http://www.csc.liv.ac.uk/~floriana/PIPS/PIPSindex.html
PROTÉGÉ: Protégé ontology editor, http://protege.stanford.edu/
SENPE, SEGG: Valoración nutricional en el anciano. Documento de Consenso. Ed., Galenitas-Nigra Trea (2007)
Serrano-Guerrero, J., Herrera-Viedma, E., Olivas, J.A., Cerezo, A., Romero, F.P.: A google wave-based fuzzy recommender system to disseminate information in university digital libraries 2.0. Inf. Sci. 181(9), 1503–1516 (2011)
Snae, C., Bruecker, M.: FOODS: A food-oriented ontology-driven system, pp. 168–176. IEEE (2008)
Tufts University, S.o.N.S.: Keep fit for life: meeting the nutritional needs of older persons. World Health Organization (2002)
Van Pinxteren, Y., Geleijnse, G., Kamsteeg, P.: Deriving a recipe similarity measure for recommending healthful meals. In: Proceedings of the 16th International Conference on Intelligent user Interfaces, IUI 2011, pp. 105–114. ACM, New York (2011)
W3C: OWL web ontology language overview, http://www.w3.org/TR/owl-features/
Wang, R.Q., Kong, F.S.: Semantic-enhanced personalized Recommender System. In: 2007 International Conference on Machine Learning and Cybernetics, vol. 7, pp. 4069–4074. IEEE (2007)
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Espín, V., Hurtado, M.V., Noguera, M., Benghazi, K. (2013). Semantic-Based Recommendation of Nutrition Diets for the Elderly from Agroalimentary Thesauri. In: Larsen, H.L., Martin-Bautista, M.J., Vila, M.A., Andreasen, T., Christiansen, H. (eds) Flexible Query Answering Systems. FQAS 2013. Lecture Notes in Computer Science(), vol 8132. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40769-7_41
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DOI: https://doi.org/10.1007/978-3-642-40769-7_41
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