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

Mogan Gim; Donghee Choi; Kana Maruyama; Jihun Choi; Hajung Kim; Donghyeon Park; Jaewoo Kang

doi:10.1145/3511808.3557092

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

Mogan Gim, Donghee Choi, Kana Maruyama, Jihun Choi, Hajung Kim, Donghyeon Park, Jaewoo Kang

Department of Computer Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

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 affinity score prediction model that quantifies 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 affinity 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 fulfilling its assistive role in cuisine domain.

Original language	English
Title of host publication	CIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management
Publisher	Association for Computing Machinery
Pages	3092-3102
Number of pages	11
ISBN (Electronic)	9781450392365
DOIs	https://doi.org/10.1145/3511808.3557092
Publication status	Published - 2022 Oct 17
Event	31st ACM International Conference on Information and Knowledge Management, CIKM 2022 - Atlanta, United States Duration: 2022 Oct 17 → 2022 Oct 21

Publication series

Name	International Conference on Information and Knowledge Management, Proceedings

Conference

Conference	31st ACM International Conference on Information and Knowledge Management, CIKM 2022
Country/Territory	United States
City	Atlanta
Period	22/10/17 → 22/10/21

Bibliographical note

Funding Information:
This research was supported by the National Research Foundation of Korea (NRF-2020R1A2C3010638), the MSIT(Ministry of Science and ICT), Korea, under the ICT Creative Consilience program(IITP-2021-2020-0-01819) supervised by the IITP(Institute for Information & Communications Technology Planning & Evaluation) and Sony AI (https://ai.sony)

Publisher Copyright:
© 2022 ACM.

Keywords

cascaded set transformer
computational cooking
food affinity score
ingredient set expansion
recipe context
recipe ideation

ASJC Scopus subject areas

Business, Management and Accounting(all)
Decision Sciences(all)

Access to Document

10.1145/3511808.3557092

Cite this

Gim, M., Choi, D., Maruyama, K., Choi, J., Kim, H., Park, D., & Kang, J. (2022). RecipeMind: Guiding Ingredient Choices from Food Pairing to Recipe Completion using Cascaded Set Transformer. In CIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management (pp. 3092-3102). (International Conference on Information and Knowledge Management, Proceedings). Association for Computing Machinery. https://doi.org/10.1145/3511808.3557092

RecipeMind: Guiding Ingredient Choices from Food Pairing to Recipe Completion using Cascaded Set Transformer. / Gim, Mogan; Choi, Donghee; Maruyama, Kana et al.
CIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management. Association for Computing Machinery, 2022. p. 3092-3102 (International Conference on Information and Knowledge Management, Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Gim, M, Choi, D, Maruyama, K, Choi, J, Kim, H, Park, D & Kang, J 2022, RecipeMind: Guiding Ingredient Choices from Food Pairing to Recipe Completion using Cascaded Set Transformer. in CIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management. International Conference on Information and Knowledge Management, Proceedings, Association for Computing Machinery, pp. 3092-3102, 31st ACM International Conference on Information and Knowledge Management, CIKM 2022, Atlanta, United States, 22/10/17. https://doi.org/10.1145/3511808.3557092

Gim M, Choi D, Maruyama K, Choi J, Kim H, Park D et al. RecipeMind: Guiding Ingredient Choices from Food Pairing to Recipe Completion using Cascaded Set Transformer. In CIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management. Association for Computing Machinery. 2022. p. 3092-3102. (International Conference on Information and Knowledge Management, Proceedings). doi: 10.1145/3511808.3557092

Gim, Mogan ; Choi, Donghee ; Maruyama, Kana et al. / RecipeMind : Guiding Ingredient Choices from Food Pairing to Recipe Completion using Cascaded Set Transformer. CIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management. Association for Computing Machinery, 2022. pp. 3092-3102 (International Conference on Information and Knowledge Management, Proceedings).

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

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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