Recipe2Vec: Multi-modal Recipe Representation Learning with Graph Neural Networks

• URL: http://arxiv.org/abs/2205.12396v1
• Date: Tue, 24 May 2022 23:04:02 GMT
• Title: Recipe2Vec: Multi-modal Recipe Representation Learning with Graph Neural Networks
• Authors: Yijun Tian, Chuxu Zhang, Zhichun Guo, Yihong Ma, Ronald Metoyer, Nitesh V. Chawla
• Abstract summary: We formalize the problem of multi-modal recipe representation learning to integrate the visual, textual, and relational information into recipe embeddings. We first present Large-RG, a new recipe graph data with over half a million nodes, making it the largest recipe graph to date. We then propose Recipe2Vec, a novel graph neural network based recipe embedding model to capture multi-modal information.
• Score: 23.378813327724686
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Learning effective recipe representations is essential in food studies. Unlike what has been developed for image-based recipe retrieval or learning structural text embeddings, the combined effect of multi-modal information (i.e., recipe images, text, and relation data) receives less attention. In this paper, we formalize the problem of multi-modal recipe representation learning to integrate the visual, textual, and relational information into recipe embeddings. In particular, we first present Large-RG, a new recipe graph data with over half a million nodes, making it the largest recipe graph to date. We then propose Recipe2Vec, a novel graph neural network based recipe embedding model to capture multi-modal information. Additionally, we introduce an adversarial attack strategy to ensure stable learning and improve performance. Finally, we design a joint objective function of node classification and adversarial learning to optimize the model. Extensive experiments demonstrate that Recipe2Vec outperforms state-of-the-art baselines on two classic food study tasks, i.e., cuisine category classification and region prediction. Dataset and codes are available at https://github.com/meettyj/Recipe2Vec.

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