A Culinary Computational Creativity System

  • Florian PinelEmail author
  • Lav R. Varshney
  • Debarun Bhattacharjya
Part of the Atlantis Thinking Machines book series (ATLANTISTM, volume 7)


Compared to artifacts in expressive or performance domains, work products resulting from scientific creativity (including culinary recipes) seem much more conducive to data-driven assessment. If such products are viewed as an assembly of constituents that follow certain association principles, one could apply computationally intensive techniques to generate many possible combinations and use automated assessors to evaluate each of them. Assembly work plans for the selected novel products could subsequently be inferred from existing records. In this chapter, we report on our efforts to build a computational creativity system for culinary recipes. After gathering data and creating a knowledge base of recipes and ingredients, the system generates ingredient combinations that satisfy user inputs such as the choice of key ingredient, desired dish, and cuisine. Once a combination has been selected with the help of novelty and quality evaluators, the system further recommends ingredient proportions using a distributional conformance method and generates recipe steps using a subgraph composition algorithm. The time durations or efforts of atomic steps are estimated by solving an inverse problem from data on complete recipes. The example of culinary recipes could be generalized and applied to other scientific domains; manufacturing products and business processes could potentially follow a similar recipe for success.


Work Product Ingredient Combination Atomic Step Ingredient Proportion Knowledge Database 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors thank the Institute of Culinary Education for their support assembling the culinary knowledge database and testing the recipes produced by the system.


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Copyright information

© Atlantis Press and the authors 2015

Authors and Affiliations

  • Florian Pinel
    • 1
    Email author
  • Lav R. Varshney
    • 2
  • Debarun Bhattacharjya
    • 1
  1. 1.IBM Thomas J. Watson Research CenterYorktown HeightsUSA
  2. 2.Coordinated Science Laboratory, Department of Electrical and Computer EngineeringUniversity of Illinois at Urbana-ChampaignUrbanaUSA

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