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A Culinary Computational Creativity System

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Computational Creativity Research: Towards Creative Machines

Part of the book series: Atlantis Thinking Machines ((ATLANTISTM,volume 7))

Abstract

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.

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Acknowledgments

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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Authors and Affiliations

  1. IBM Thomas J. Watson Research Center, Yorktown Heights, New York, USA

    Florian Pinel & Debarun Bhattacharjya

  2. Coordinated Science Laboratory, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, USA

    Lav R. Varshney

Authors
  1. Florian Pinel
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  2. Lav R. Varshney
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  3. Debarun Bhattacharjya
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Corresponding author

Correspondence to Florian Pinel .

Editor information

Editors and Affiliations

  1. Institute of Cognitive Science, University of Osnabrück, Osnabrück, Germany

    Tarek R. Besold

  2. IIIA-CSIC, Bellaterra (Barcelona), Spain

    Marco Schorlemmer

  3. CISA, School of Informatics, University of Edinburgh, Edinburgh, United Kingdom

    Alan Smaill

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Pinel, F., Varshney, L.R., Bhattacharjya, D. (2015). A Culinary Computational Creativity System. In: Besold, T., Schorlemmer, M., Smaill, A. (eds) Computational Creativity Research: Towards Creative Machines. Atlantis Thinking Machines, vol 7. Atlantis Press, Paris. https://doi.org/10.2991/978-94-6239-085-0_16

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  • DOI: https://doi.org/10.2991/978-94-6239-085-0_16

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  • Publisher Name: Atlantis Press, Paris

  • Print ISBN: 978-94-6239-084-3

  • Online ISBN: 978-94-6239-085-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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