Computational gastronomy: A data science approach to food

Goel, Mansi; Bagler, Ganesh

doi:10.1007/s12038-021-00248-1

Cited by 6 publications

(3 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The application of data-driven strategies for investigating gastronomic questions has opened up an all-new paradigm for the study of food and cooking. Computational Gastronomy is a data science that blends food, data, and computation towards achieving data-driven food innovations 6 . A data and computing-centric approach will enable the transformation of the food landscape leading to better public health and nutrition.…”

Section: Cooking As An Artmentioning

confidence: 99%

See 1 more Smart Citation

Computational gastronomy: capturing culinary creativity by making food computable

Bagler,

Goel

2024

npj Syst Biol Appl

View full text Add to dashboard Cite

Cooking, a quintessential creative pursuit, holds profound significance for individuals, communities, and civilizations. Food and cooking transcend mere sensory pleasure to influence nutrition and public health outcomes. Inextricably linked to culinary and cultural heritage, food systems play a pivotal role in sustainability and the survival of life on our planet. Computational Gastronomy is a novel approach for investigating food through a data-driven paradigm. It offers a systematic, rule-based understanding of culinary arts by scrutinizing recipes for taste, nutritional value, health implications, and environmental sustainability. Probing the art of cooking through the lens of computation will open up a new realm of possibilities for culinary creativity. Amidst the ongoing quest for imitating creativity through artificial intelligence, an interesting question would be, ‘Can a machine think like a Chef?’ Capturing the experience and creativity of a chef in an AI algorithm presents an exciting opportunity for generating a galaxy of hitherto unseen recipes with desirable culinary, flavor, nutrition, health, and carbon footprint profiles.

show abstract

Section: Cooking As An Artmentioning

confidence: 99%

“…In the last nine years, our lab (Complex Systems Laboratory, IIIT-Delhi: https://cosylab.iiitd.edu.in ) has built databases 7 – 11 and created a body of knowledge 6 – 31 that has contributed to the growth of Computational Gastronomy–the data science of food, flavors, nutrition, health, and sustainability (Fig. 1a ).…”

Section: Cooking As An Artmentioning

confidence: 99%

Computational gastronomy: capturing culinary creativity by making food computable

Bagler,

Goel

2024

npj Syst Biol Appl

View full text Add to dashboard Cite

show abstract

“…Computational approaches for assisting recipe ideation process have recently become necessary to solve these issues in culinary domain [21]. For instance, Kitchenette predicts food pairing scores [40] and RecipeBowl retrieves the best ingredient given a nearly completed recipe [24] which are deemed as earliest and latest stage of recipe ideation respectively.…”

Section: Introductionmentioning

confidence: 99%

RecipeMind: Guiding Ingredient Choices from Food Pairing to Recipe Completion using Cascaded Set Transformer

Gim

Choi

Maruyama

et al. 2022

Proceedings of the 31st ACM International Conference on Information &Amp; Knowledge Management

View full text Add to dashboard Cite

We propose a computational approach for recipe ideation, a downstream task that helps users select and gather ingredients for creating dishes. To perform this task, we developed RecipeMind, a food anity score prediction model that quanties the suitability of adding an ingredient to set of other ingredients. We constructed a large-scale dataset containing ingredient co-occurrence based scores to train and evaluate RecipeMind on food anity score prediction. Deployed in recipe ideation, RecipeMind helps the user expand an initial set of ingredients by suggesting additional ingredients. Experiments and qualitative analysis show RecipeMind's potential in fullling its assistive role in cuisine domain.

show abstract

Computational gastronomy: A study to test the food pairing hypothesis in Turkish cuisine

Doğan,

Değerli

2023

International Journal of Gastronomy and Food Science

View full text Add to dashboard Cite

Computational gastronomy: A data science approach to food

Cited by 6 publications

References 47 publications

Computational gastronomy: capturing culinary creativity by making food computable

Computational gastronomy: capturing culinary creativity by making food computable

RecipeMind: Guiding Ingredient Choices from Food Pairing to Recipe Completion using Cascaded Set Transformer

Computational gastronomy: A study to test the food pairing hypothesis in Turkish cuisine

Contact Info

Product

Resources

About