论文标题
配方：使用级联套装变压器从食物配对到食谱完成的指导成分选择
RecipeMind: Guiding Ingredient Choices from Food Pairing to Recipe Completion using Cascaded Set Transformer
论文作者
论文摘要
我们提出了一种用于食谱概念的计算方法，这是一项下游任务，可帮助用户选择和收集创建菜肴的成分。为了执行此任务，我们开发了配对，这是一种食品亲和力评分预测模型，可量化为其他成分添加成分的适用性。我们构建了一个大规模数据集，其中包含基于成分的共发生分数，以训练和评估食物亲和力评分预测的对选择。 Copemind部署在食谱构想中，通过建议其他成分来帮助用户扩展一组初始成分。实验和定性分析表明，配方在履行其在美食领域中的辅助作用方面的潜力。
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.
