Improving Ingredient Substitution using Formal Concept Analysis and Adaptation of Ingredient Quantities with Mixed Linear Optimization

Emmanuelle Gaillard (1, 2) , Jean Lieber (2, 1) , Emmanuel Nauer (2, 1)

1 ORPAILLEUR - Knowledge representation, reasonning
2 UL - Université de Lorraine

This paper presents the participation of the Taaable team to the 2015 Computer Cooking Contest. The Taaable system addresses the mixology and the sandwich challenges. For the mixology challenge, the 2014 Taaable system was extended in two ways. First, a formal concept analysis approach is used to improve the ingredient substitution, which must take into account a limited set of available foods. Second, the adaptation of the ingredient quantities has also been improved in order to be more realistic with a real cooking setting. The adaptation of the ingredient quantities is based on a mixed linear optimization. The team also applied Taaable to the sandwich challenge.

Mots clés: mixed linear optimization; adaptation of ingredient quantities; case-based reasoning; formal concept analysis

Domaines: Informatique

Emmanuelle Gaillard, Jean Lieber, Emmanuel Nauer. Improving Ingredient Substitution using Formal Concept Analysis and Adaptation of Ingredient Quantities with Mixed Linear Optimization. Computer Cooking Contest Workshop, Sep 2015, Frankfort, Germany. ⟨hal-01240383⟩