A hybrid approach for detecting prerequisite relations in multi-modal food recipes

• Main Authors: PAN, Liangming, CHEN, Jingjing, LIU, Shaoteng, NGO, Chong-wah, KAN, Min-Yen, CHUA, Tat-Seng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Feature extraction; Training; Task analysis; Semantics; Pipelines; Deep learning; Predictive models; Food recipes; cooking workflow; prerequisite trees; multi-modal fusion; cause-and-effect reasoning; deep learning; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/7927; https://ink.library.smu.edu.sg/context/sis_research/article/8930/viewcontent/TMM20_Paper__1_.pdf
• Institution: Singapore Management University

Modeling the structure of culinary recipes is the core of recipe representation learning. Current approaches mostly focus on extracting the workflow graph from recipes based on text descriptions. Process images, which constitute an important part of cooking recipes, has rarely been investigated in r...