You are What You Eat: Exploring Rich Recipe Information for Cross-Region Food Analysis

	You are What You Eat: Exploring Rich Recipe Information for Cross-Region Food Analysis
	Weiqing Min; Bing-Kun Bao; Shuhuan Mei; Yaohui Zhu; Yong Rui; Shuqiang Jiang
发表期刊	IEEE Transactions on Multimedia
	2017-10
期号	99 页码:1-1
摘要	Cuisine is a style of cooking and usually associated with a specific geographic region. Recipes from different cuisines shared on the web are an indicator of culinary cultures in different countries. Therefore, analysis of these recipes can lead to deep understanding of food from the cultural perspective. In this paper, we perform the first cross-region recipe analysis by jointly using the recipe ingredients, food images and attributes such as the cuisine and course (e.g., main dish and dessert). For that solution, we propose a culinary culture analysis framework to discover the topics of ingredient bases and visualize them to enable various applications. We firstly propose a probabilistic topic model to discover cuisine-course specific topics. The manifold ranking method is then utilized to incorporate deep visual features to retrieve food images for topic visualization. At last, we applied the topic modeling and visualization method for three applications: (1) multi-modal cuisine summarization with both recipe ingredients and images, (2) cuisine-course pattern analysis including topic-specific cuisine distribution and cuisine-specific course distribution of topics, and (3) cuisine recommendation for both cuisine-oriented and ingredient-oriented queries. Through these three applications, we can analyze the culinary cultures at both macro and micro levels. We conduct the experiment on a recipe database Yummly-66K with 66,615 recipes from 10 cuisines in Yummly. Qualitative and quantitative evaluation results have validated the effectiveness of topic modeling and visualization, and demonstrated the advantage of the framework in utilizing rich recipe information to analyze and interpret the culinary cultures from different regions.
关键词	Non
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/19859
专题	多模态人工智能系统全国重点实验室_多媒体计算
推荐引用方式 GB/T 7714	Weiqing Min,Bing-Kun Bao,Shuhuan Mei,et al. You are What You Eat: Exploring Rich Recipe Information for Cross-Region Food Analysis[J]. IEEE Transactions on Multimedia,2017(99):1-1.
APA	Weiqing Min,Bing-Kun Bao,Shuhuan Mei,Yaohui Zhu,Yong Rui,&Shuqiang Jiang.(2017).You are What You Eat: Exploring Rich Recipe Information for Cross-Region Food Analysis.IEEE Transactions on Multimedia(99),1-1.
MLA	Weiqing Min,et al."You are What You Eat: Exploring Rich Recipe Information for Cross-Region Food Analysis".IEEE Transactions on Multimedia .99(2017):1-1.

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