An overview of recommender systems in the healthy food domain

Thi Ngoc Trang Tran1, Müslüm Atas1, Alexander Felfernig1, Martin Stettinger1
1Applied Software Engineering Group, Institute for Software Technology, Graz University of Technology, Graz, Austria

Tóm tắt

Từ khóa


Tài liệu tham khảo

Aberg, J. (2006). Dealing With malnutrition: A meal planning system for elderly.

Adomavicius, G., Bockstedt, J., Curley, S., & Zhang, J. (2011). Recommender systems, consumer preferences, and anchoring effects, 811, 35–42.

Aizawa, K., de Silva, G.C., Ogawa, M., & Sato, Y. (2010). Food log by snapping and processing images, 2010 16th international conference on virtual systems and multimedia, IEEE (pp. 71–74).

Ardissono, L., Goy, A., Petrone, G., Segnan, M., & Torasso, P. (2003). Intrigue: Personalized recommendation of tourist attractions for desktop and handset devices. Applied Artificial Intelligence, 17(8), 687–714.

Asanov, D. (2011). Algorithms and methods in recommender systems Berlin Institute of Technology. Germany: Berlin.

Balabanović, M., & Shoham, Y. (1997). Fab: Content-based, collaborative recommendation. Communications of the ACM, 40(3), 66–72.

Berkovsky, S., & Freyne, J. (2010). Group-based recipe recommendations: Analysis of data aggregation strategies, Proceedings of the fourth ACM conference on recommender systems, RecSys ’10 (pp. 111–118).

Bokde, D.K., Girase, S., & Mukhopadhyay, D. (2015). Role of matrix factorization model in collaborative filtering algorithm: A survey. CoRR abs/1503.07475.

Bridge, D., Göker, M.H., McGinty, L., & Smyth, B. (2005). Case-based recommender systems. Knowl Eng Review, 20(3), 315–320.

Burke, R. (2000). Knowledge-based recommender systems, Encyclopedia of library and information systems, vol 69, Marcel Dekker (pp. 180–200).

Burke, R. (2002). Hybrid recommender systems: Survey and experiments. User Modeling and User-Adapted Interaction, 12(4), 331–370.

Burke, R., Felfernig, A., & Göker, M.H. (2011). Recommender systems: an overview. AI Magazine, 32, 13–18.

Cantador, I., & Castells, P. (2012). Group recommender systems: New perspectives in the social web, Recommender systems for the social Web, intelligent systems reference library, vol 32, Springer Berlin Heidelberg (pp. 139–157).

Castro, J., Quesada, F.J., Palomares, I., & Martínez-López, L. (2015). A consensus-driven group recommender system. International Journal of Intelligent Systems, 30(8), 887–906.

Chen, L., & Pu, P. (2012). Critiquing-based recommenders: survey and emerging trends. User Model User-Adapt Interact, 22(1-2), 125–150.

Crossen, A., Budzik, J., & Hammond, K.J. (2002). Flytrap: Intelligent group music recommendation, Proceedings of the 7th international conference on intelligent user interfaces, ACM, New York, NY, USA, IUI ’02 (pp. 184–185).

Ekstrand, M.D., Riedl, J.T., & Konstan, J.A. (2011). Collaborative filtering recommender systems. Found Trends Hum-Comput Interact, 4(2), 81–173.

El-Dosuky, M.A., Rashad, M.Z., Hamza, T.T., & El-Bassiouny, A.H. (2012). Food recommendation using ontology and heuristics, AMLTA, Springer, communications in computer and information science, (Vol. 322 pp. 423–429).

Elahi, M., Ge, M., Ricci, F., Massimo, D., & Berkovsky, S. (2014). Interactive food recommendation for groups, RECSYS, Vol. 1247.

Elahi, M., Ge, M., Ricci, F., Fernández-Tobías, I., Berkovsky, S., & Massimo, D. (2015). Interaction design in a mobile food recommender system, IntRS@recsys, CEUR-WS.org, CEUR workshop proceedings, (Vol. 1438 pp. 49–52).

Elsweiler, D., Harvey, M., Ludwig, B., & Said, A. (2015). Bringing the healthy into food recommenders. In Ge, M., & Ricci, F. (Eds.), DMRS, CEUR-WS.org, CEUR workshop proceedings, (Vol. 1533 pp. 33–36).

Felfernig, A. (2014). Biases in decision making, Proceedings of the first international workshop on decision making and recommender systems (DMRS2014), Bolzano, Italy, September 18-19, 2014., vol 1278, CEUR Proceedings (pp. 32–37).

Felfernig, A., & Burke, R. (2008). Constraint-based recommender systems: Technologies and research issues, Proceedings of the 10th international conference on electronic commerce, ACM, New York, NY, USA, ICEC ’08 (pp. 3:1–3:10).

Felfernig, A., Teppan, E., & Gula, B. (2006). Knowledge-based recommender technologies for marketing and sales. Pattern Recognition and Artificial Intelligence, 21 (2), 1–22.

Felfernig, A., Friedrich, G., Jannach, D., & Zanker, M. (2011). Recommender systems handbook, Springer US, chapter: Developing Constraint-based Recommenders, 187–215.

Felfernig, A., Zehentner, C., Ninaus, G., Grabner, H., Maalej, W., Pagano, D., Weninger, L., & Reinfrank, F. (2012). Advances in user modeling, Springer Berlin Heidelberg, chapter: Group Decision Support for Requirements Negotiation, 105–116.

Felfernig, A., Hotz, L., Bagley, C., & Tiihonen, J. (2014a). Knowledge-based Configuration: From Research to Business Cases, 1st edn. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc.

Felfernig, A., Stettinger, M., Ninaus, G., Jeran, M., Reiterer, S., Falkner, A.A., Leitner, G., & Tiihonen, J. (2014b). Towards open configuration, Proceedings of the 16th international configuration workshop, Novi Sad, Serbia, September 25-26, 2014 (pp. 89–94).

Freyne, J., & Berkovsky, S. (2010). Intelligent food planning: personalized recipe recommendation, Proceedings of the 15th international conference on Intelligent user interfaces, ACM, New York, NY, USA, IUI ’10 (pp. 321–324).

Freyne, J., Berkovsky, S., & Smith, G. (2011). Recipe recommendation: Accuracy and reasoning, 19th international conference, UMAP 2011, Girona, Spain, July 11-15, 2011., Springer Berlin Heidelberg (pp. 99–110).

Harvey, M., & Elsweiler, D. (2015). Automated recommendation of healthy, personalised meal plans, Proceedings of the 9th ACM conference on recommender systems, ACM, New York, NY, USA, RecSys ’15 (pp. 327–328).

Hoxmeier, J.A.D.P., & Manager, C.D. (2000). System response time and user satisfaction: An experimental study of browser-based applications, Proceedings of the association of information systems americas conference (pp. 10–13).

Jameson, A. (2004). More than the sum of its members: Challenges for group recommender systems, Proceedings of the working conference on advanced visual interfaces, ACM, New York, NY, USA, AVI ’04 (pp. 48–54).

Jameson, A., & Smyth, B. (2007). The adaptive web. chap Recommendation to Groups, 596–627.

Knowler, W., Barrett-Connor, E., Fowler, S., Hamman, R., Lachin, J., Walker, E., & Nathan, D. (2002). Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. New England Journal of Medicine, 346(6), 393–403.

Koren, Y., Bell, R., & Volinsky, C. (2009). Matrix factorization techniques for recommender systems. Computer, 42(8), 30–37.

Kuo, F.F., Li, C.T., Shan, M.K., & Lee, S.Y. (2012). Intelligent menu planning: Recommending set of recipes by ingredients, Proceedings of the ACM multimedia 2012 workshop on multimedia for cooking and eating activities, ACM, New York, NY, USA, CEA ’12 (pp. 1–6).

Lang, K. (1995). Newsweeder: Learning to filter netnews. In Prieditis, A., & Russell, S.J. (Eds.), Machine learning, proceedings of the twelfth international conference on machine learning, Tahoe City, California, USA, July 9-12, 1995, Morgan Kaufmann (pp. 331–339).

Lieberman, H., Van Dyke, N.W., & Vivacqua, A.S. (1999). Let’s browse: A collaborative web browsing agent, Proceedings of the 4th international conference on intelligent user interfaces, ACM, New York, NY, USA, IUI ’99 (pp. 65–68).

Mankoff, J., Hsieh, G., Hung, H.C., Lee, S., & Nitao, E. (2002). Using low-cost sensing to support nutritional awareness, Ubicomp, Springer, lecture notes in computer science, (Vol. 2498 pp. 371–376).

Masthoff, J. (2004). Group modeling: Selecting a sequence of television items to suit a group of viewers. User Modeling and User-Adapted Interaction, 14(1), 37–85.

Masthoff, J. (2011). Group recommender systems: Combining individual models, Recommender systems handbook, Springer (pp. 677–702).

McCarthy, J.F., & Anagnost, T.D. (1998). Musicfx: An arbiter of group preferences for computer supported collaborative workouts, Proceedings of the 1998 ACM conference on computer supported cooperative work, ACM, New York, NY, USA, CSCW ’98 (pp. 363–372).

McCarthy, K., Salamó, M., Coyle, L., McGinty, L., Smyth, B., & Nixon, P. (2006). Group recommender systems: A critiquing based approach, Proceedings of the 11th international conference on intelligent user interfaces, ACM, New York, NY, USA, IUI ’06 (pp. 267–269).

Mika, S. (2011). Challenges for nutrition recommender systems. CEUR-WS.org, Workshop Proceedings on Context Aware Intelligent Assistance, 25–33.

Mooney, R.J., & Roy, L. (2000). Content-based book recommending using learning for text categorization. 195–204.

O’Connor, M., Cosley, D., Konstan, J.A., & Riedl, J. (2001). Polylens: A recommender system for groups of users, Proceedings of the seventh conference on European conference on computer supported cooperative work, Kluwer Academic Publishers, Norwell, MA, USA, ECSCW’01 (pp. 199– 218).

Pazzani, M.J., Muramatsu, J., & Billsus, D. (1996). Syskill and webert: Identifying interesting web sites. In Clancey, W.J., & Weld, D.S. (Eds.), AAAI/IAAI, Vol. 1, AAAI Press / The MIT Press (pp. 54–61).

Ricci, F., Rokach, L., Shapira, B., & Kantor, P.B. (2010). Recommender Systems Handbook, 1st edn. New York, NY, USA: Springer-Verlag New York, Inc.

Robertson, A. (2004). Food and health in europe: a new basis for action. Academic Search Complete, WHO Regional Office for Europe.

Roza, A.M., & Shizgal, H.M. (1984). The harris benedict equation reevaluated: resting energy requirements and the body cell mass. The American Journal of Clinical nutrition, 40(1), 168–182.

Sarwar, B., Karypis, G., Konstan, J., & Riedl, J. (2001). Item-based collaborative filtering recommendation algorithms, Proceedings of the 10th international conference on World Wide Web, ACM, New York, NY, USA, WWW ’01 (pp. 285–295).

Smith, R.B., Hixon, R., & Horan, B. (1998). Supporting flexible roles in a shared space, Proceedings of the 1998 ACM conference on computer supported cooperative work, ACM, New York, NY, USA, CSCW ’98 (pp. 197–206).

Snooks, M. (2009). Health Psychology: Biological, Psychological, and Sociocultural Perspectives, Jones & Bartlett Learning chapter 5: Applications of Health Psychology to Eating Behaviors: Improving health through nutritional changes.

Stettinger, M. (2014). Choicla: Towards domain-independent decision support for groups of users, Proceedings of the 8th ACM conference on recommender systems, ACM, New York, NY, USA, RecSys ’14 (pp. 425–428).

Stettinger, M., Felfernig, A., Leitner, G., Reiterer, S., & Jeran, M. (2015). Counteracting serial position effects in the choicla group decision support environment, Proceedings of the 20th international conference on intelligent user interfaces. IUI 2015 (ACM - San Francisco) (pp. 148–157).

Svensson, M., Laaksolahti, J., Höök, K., & Waern, A. (2000). A recipe based on-line food store, Proceedings of the 5th international conference on intelligent user interfaces, ACM, New York, NY, USA, IUI ’00 (pp. 260–263).

Thuy Ngoc Nguyen, F.R. (2017). A chat-based group recommender system for tourism. Information and Communication Technologies, 17–30.

Tintarev, N., & Masthoff, J. (2007). A survey of explanations in recommender systems, Proceedings of the 2007 IEEE 23rd international conference on data engineering workshop, IEEE Computer Society, Washington, DC, USA, ICDEW ’07 (pp. 801–810).

Ueta, T., Iwakami, M., & Ito, T. (2011). A recipe recommendation system based on automatic nutrition information extraction, Proceedings of the 5th international conference on knowledge science, engineering and management, Springer-Verlag, Berlin, Heidelberg, KSEM’11 (pp. 79–90).

Van Pinxteren, Y., Geleijnse, G., & Kamsteeg, P. (2011). Deriving a recipe similarity measure for recommending healthful meals, Proceedings of the 16th international conference on intelligent user interfaces, ACM, New York, NY, USA, IUI ’11 (pp. 105–114).

Yu, Z., Zhou, X., Hao, Y., & Gu, J. (2006). Tv program recommendation for multiple viewers based on user profile merging. User Modeling and User-Adapted Interaction, 16(1), 63–82.