CASIA OpenIR  > 模式识别国家重点实验室  > 多媒体计算与图形学
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
Source PublicationIEEE Transactions on Multimedia
2017-10
Issue99Pages:1-1
AbstractCuisine 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.
KeywordNon
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/19859
Collection模式识别国家重点实验室_多媒体计算与图形学
Recommended Citation
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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