Abstract
Recommender systems are needed to find food items of one’s interest. This paper reviews recommender systems and recommendation methods, then propose a food personalization framework based on adaptive hypermedia and extend Hermes framework with food recommendation functionality. Moreover, it combines TF-IDF term extraction method with cosine similarity measure. Healthy heuristics and standard food database are incorporated into the knowledgebase. Based on the performed evaluation, we conclude that semantic recommender systems in general outperform traditional recommenders systems with respect to accuracy, precision, and recall, and that the proposed recommender has a better F-measure than existing semantic recommenders.
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
Preview
Unable to display preview. Download preview PDF.
References
Mika, S.: Challenges for Nutrition Recommender Systems. In: Proceedings of the 2nd Workshop on Context Aware Intel. Assistance, Berlin, Germany, pp. 25–33 (October 2011)
Keogh, R.H., White, I.R.: Allowing for never and episodic consumers when correcting for error in food record measurements of dietary intake. Biostatistics (March 2011)
van Pinxteren, Y., Geleijnse, G., Kamsteeg, P.: Deriving a recipe similarity measure for recommending healthful meals. In: Proc. of the 16th International Conference on Intelligent User Interfaces, IUI 2011, pp. 105–114. ACM, New York (2011)
Becker, M.H., Maiman, L.A.: Strategies for enhancing patient compliance. Journal of Community Health 6(2), 113–135 (1980)
Wansink, B.: Mindless Eating—Why We Eat More Than We Think. Bantam-Dell, New York (2006)
Hammond, K.: Chef: A model of case-based planning. In: Proceedings of the National Conference on AI (1986)
Hinrichs, T.: Strategies for adaptation and recovery in a design problem solver. In: Proceedings of the Workshop on Case-Based Reasoning (1989)
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, New York (2010)
Aberg, J.: Dealing with malnutrition: A meal planning system for elderly. In: AAAI, Spring Symposium on Argumentation for Consumers of Health Care (2006)
Mankoff, J., Hsieh, G., Hung, H.C., Nitao, E.: Using Low-Cost Sensing to Support Nutritional Awareness. In: Borriello, G., Holmquist, L.E. (eds.) UbiComp 2002. LNCS, vol. 2498, pp. 371–378. Springer, Heidelberg (2002)
Chi, P., Chen, J., Chu, H., Lo, J.: Enabling calorie-aware cooking in a smart kitchen. In: Proc. of the 3rd International Conference on Persuasive Technology, June 04-06 (2008)
Kitamura, K., de Silva, C., Yamasaki, T., Aizawa, K.: Image processing based approach to food balance analysis for personal food logging. In: 2010 IEEE International Conference on Multimedia and Expo (ICME), pp. 625–630 (July 2010)
Karg, G., Bognar, A., Ohmayer, G.: Nutrient content of composite food: a survey of methods. In: Proceedings of European Seminar of EOQC Food Section, Budapest, pp. 148–179 (1986)
Powers, P.M., Hoover, L.W.: Calculating the nutrient composition of recipes with computers. J. Am. Diet. Assoc. 89, 224–232 (1989)
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, New York (2010)
Adomavicius, G., Tuzhilin, A.: Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions. IEEE Transactions on Knowledge and Data Engineering 17(6), 734–749 (2005)
Salton, G., Buckley, C.: Term-Weighting Approaches in Automatic Text Retrieval. Information Processing and Management 24(5), 513–523 (1988)
IJntema, W., Goossen, F., Frasincar, F., Hogenboom, F.: Ontology-Based News Recommendation. In: EDBT/ICDT International Workshop on Business Intelligence and the Web (BEWEB 2010). ACM (2010)
Jaccard, P.: Étude Comparative de la Distribution Florale dans une Portion des Alpes et des Jura. Bulletin del la Société Vaudoise des Sciences Naturelles 37, 547–579 (1901)
Getahun, F., Tekli, J., Chbeir, R., Viviani, M., Yetongnon, K.: Relating RSS News/Items. In: Gaedke, M., Grossniklaus, M., Díaz, O. (eds.) ICWE 2009. LNCS, vol. 5648, pp. 442–452. Springer, Heidelberg (2009)
Bra, P.D., Aerts, A.T.M., Houben, G.J., Wu, H.: Making General-Purpose Adaptive Hypermedia Work. In: World Conference on the WWW and Internet (WebNet 2000), pp. 117–123 (2000)
Borsje, J., Levering, L., Frasincar, F.: Hermes: a Semantic Web-Based News Decision Support System. In: 23rd Annual ACM Symposium on Applied Computing, SAC 2008, pp. 2415–2420 (2008)
Bechhofer, S., van Harmelen, F., Hendler, J., Horrocks, I., McGuinness, D.L., Patel-Schneider, P.F., et al.: OWL Web Ontology Language Reference W3C Recommendation, February 10 (2004)
http://ndb.nal.usda.gov/ndb/foods/list (accessed July 24, 2012)
Buckley, C., Allan, J., Salton, G.: Automatic Routing and Retrieval Using Smart: TREC-2. Information Porcessing and Management 31(3), 315–326 (1995)
Singhal, A., Buckley, C., Mitra, M.: Pivoted Document Length Normalization. In: 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 1996), pp. 21–29. ACM (1996)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
El-Dosuky, M.A., Rashad, M.Z., Hamza, T.T., EL-Bassiouny, A.H. (2012). Food Recommendation Using Ontology and Heuristics. In: Hassanien, A.E., Salem, AB.M., Ramadan, R., Kim, Th. (eds) Advanced Machine Learning Technologies and Applications. AMLTA 2012. Communications in Computer and Information Science, vol 322. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35326-0_42
Download citation
DOI: https://doi.org/10.1007/978-3-642-35326-0_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35325-3
Online ISBN: 978-3-642-35326-0
eBook Packages: Computer ScienceComputer Science (R0)