Kitchenette: Predicting and ranking food ingredient pairings using siamese neural networks

Donghyeon Park, Keonwoo Kim, Yonggyu Park, Jungwoon Shin, Jaewoo Kang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

As a vast number of ingredients exist in the culinary world, there are countless food ingredient pairings, but only a small number of pairings have been adopted by chefs and studied by food researchers. In this work, we propose KitcheNette which is a model that predicts food ingredient pairing scores and recommends optimal ingredient pairings. KitcheNette employs Siamese neural networks and is trained on our annotated dataset containing 300K scores of pairings generated from numerous ingredients in food recipes. As the results demonstrate, our model not only outperforms other baseline models, but also can recommend complementary food pairings and discover novel ingredient pairings.

Original languageEnglish
Title of host publicationProceedings of the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019
EditorsSarit Kraus
PublisherInternational Joint Conferences on Artificial Intelligence
Pages5930-5936
Number of pages7
ISBN (Electronic)9780999241141
Publication statusPublished - 2019 Jan 1
Event28th International Joint Conference on Artificial Intelligence, IJCAI 2019 - Macao, China
Duration: 2019 Aug 102019 Aug 16

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence
Volume2019-August
ISSN (Print)1045-0823

Conference

Conference28th International Joint Conference on Artificial Intelligence, IJCAI 2019
CountryChina
CityMacao
Period19/8/1019/8/16

Fingerprint

Neural networks

ASJC Scopus subject areas

  • Artificial Intelligence

Cite this

Park, D., Kim, K., Park, Y., Shin, J., & Kang, J. (2019). Kitchenette: Predicting and ranking food ingredient pairings using siamese neural networks. In S. Kraus (Ed.), Proceedings of the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019 (pp. 5930-5936). (IJCAI International Joint Conference on Artificial Intelligence; Vol. 2019-August). International Joint Conferences on Artificial Intelligence.

Kitchenette : Predicting and ranking food ingredient pairings using siamese neural networks. / Park, Donghyeon; Kim, Keonwoo; Park, Yonggyu; Shin, Jungwoon; Kang, Jaewoo.

Proceedings of the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019. ed. / Sarit Kraus. International Joint Conferences on Artificial Intelligence, 2019. p. 5930-5936 (IJCAI International Joint Conference on Artificial Intelligence; Vol. 2019-August).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Park, D, Kim, K, Park, Y, Shin, J & Kang, J 2019, Kitchenette: Predicting and ranking food ingredient pairings using siamese neural networks. in S Kraus (ed.), Proceedings of the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019. IJCAI International Joint Conference on Artificial Intelligence, vol. 2019-August, International Joint Conferences on Artificial Intelligence, pp. 5930-5936, 28th International Joint Conference on Artificial Intelligence, IJCAI 2019, Macao, China, 19/8/10.
Park D, Kim K, Park Y, Shin J, Kang J. Kitchenette: Predicting and ranking food ingredient pairings using siamese neural networks. In Kraus S, editor, Proceedings of the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019. International Joint Conferences on Artificial Intelligence. 2019. p. 5930-5936. (IJCAI International Joint Conference on Artificial Intelligence).
Park, Donghyeon ; Kim, Keonwoo ; Park, Yonggyu ; Shin, Jungwoon ; Kang, Jaewoo. / Kitchenette : Predicting and ranking food ingredient pairings using siamese neural networks. Proceedings of the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019. editor / Sarit Kraus. International Joint Conferences on Artificial Intelligence, 2019. pp. 5930-5936 (IJCAI International Joint Conference on Artificial Intelligence).
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