TY - GEN
T1 - RecipeMind
T2 - 31st ACM International Conference on Information and Knowledge Management, CIKM 2022
AU - Gim, Mogan
AU - Choi, Donghee
AU - Maruyama, Kana
AU - Choi, Jihun
AU - Kim, Hajung
AU - Park, Donghyeon
AU - Kang, Jaewoo
N1 - 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.
PY - 2022/10/17
Y1 - 2022/10/17
N2 - 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.
AB - 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.
KW - cascaded set transformer
KW - computational cooking
KW - food affinity score
KW - ingredient set expansion
KW - recipe context
KW - recipe ideation
UR - http://www.scopus.com/inward/record.url?scp=85140832146&partnerID=8YFLogxK
U2 - 10.1145/3511808.3557092
DO - 10.1145/3511808.3557092
M3 - Conference contribution
AN - SCOPUS:85140832146
T3 - International Conference on Information and Knowledge Management, Proceedings
SP - 3092
EP - 3102
BT - CIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management
PB - Association for Computing Machinery
Y2 - 17 October 2022 through 21 October 2022
ER -