基于神经网络的地方菜系风格转换系统
A neural network system for transformation of regional cuisine style
摘要：
我们提出了一种新的系统，它可以将食谱转换为任何选定的区域风格（例如，日本、地中海或意大利）。这一制度有两个特点。首先，该系统可以识别任何选定的食谱的区域美食风格混合的程度，并使用重心牛顿图可视化这种区域美食风格混合。第二，系统可以通过扩展的word2vec模型来建议配料替换，使得食谱对于任何选定的区域烹饪风格变得更加真实。利用Yummly的大量食谱，一个例子展示了所提出的系统如何将传统的日本食谱寿喜烧转变为法国风格。
英文摘要：
We propose a novel system which can transform a recipe into any selected regional style (e.g., Japanese, Mediterranean, or Italian). This system has two characteristics. First the system can identify the degree of regional cuisine style mixture of any selected recipe and visualize such regional cuisine style mixtures using barycentric Newton diagrams. Second, the system can suggest ingredient substitutions through an extended word2vec model, such that a recipe becomes more authentic for any selected regional cuisine style. Drawing on a large number of recipes from Yummly, an example shows how the proposed system can transform a traditional Japanese recipe, Sukiyaki, into French style.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
