Intelligent menu planning: recommending set of recipes by ingredients

With the growth of recipe sharing services, online cooking recipes associated with ingredients and cooking procedures are available. Many recipe sharing sites have devoted to the development of recipe recommendation mechanism. However, there is a need for users to plan menu of meals by ingredients. While most research on food related research has been on recipe recommendation and retrieval, little research has been done on menu planning. In this paper, we investigate an intelligent menu planning mechanism which recommending sets of recipes by user-specified ingredients. Those recipes which are well-accompanied and contain the query ingredients are returned. We propose a graph-based algorithm for menu planning. The proposed approach constructs a recipe graph to capture the co-occurrence relationships between recipes from collection of menus. A menu is generated by approximate Steiner Tree Algorithm on the constructed recipe graph. Evaluation of menu collections from Food.com shows that the proposed approach achieves encouraging results.

[1]  Yu Yang,et al.  Substructure similarity measurement in chinese recipes , 2008, WWW.

[2]  Mutsuo Sano,et al.  A cooking support system for people with higher brain dysfunction , 2009, CEA '09.

[3]  Shlomo Berkovsky,et al.  Intelligent food planning: personalized recipe recommendation , 2010, IUI '10.

[4]  Juergen Wagner,et al.  Guidance and support for healthy food preparation in an augmented kitchen , 2011, CaRR '11.

[5]  Ichiro Kobayashi,et al.  Recipe recommendation for a diet considering a user's schedule and the balance of nourishment , 2009, 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems.

[6]  Youri van Pinxteren,et al.  Deriving a recipe similarity measure for recommending healthful meals , 2011, IUI '11.

[7]  Atsushi Fujii,et al.  A system for supporting dietary habits: planning menus and visualizing nutritional intake balance , 2010, ICUIMC '10.

[8]  Shinsuke Nakajima,et al.  User's food preference extraction for personalized cooking recipe recommendation , 2011 .

[9]  Mu Zhu,et al.  Content-boosted matrix factorization for recommender systems: experiments with recipe recommendation , 2011, RecSys '11.

[10]  Shou-De Lin,et al.  Context-based people search in labeled social networks , 2011, CIKM '11.

[11]  Janusz Sobecki,et al.  Application of Hybrid Recommendation in Web-Based Cooking Assistant , 2006, KES.

[12]  Hiroshi Murase,et al.  Finding replaceable materials in cooking recipe texts considering characteristic cooking actions , 2009, CEA '09.

[13]  Kristina Höök,et al.  Designing and evaluating kalas: A social navigation system for food recipes , 2005, TCHI.

[14]  Haoran Xie,et al.  A Hybrid Semantic Item Model for Recipe Search by Example , 2010, 2010 IEEE International Symposium on Multimedia.

[15]  Gabriele Reich,et al.  Beyond Steiner's Problem: A VLSI Oriented Generalization , 1989, WG.