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: hxploring Rich Recipe Information for Cross-Region Food Analysis
Min, Weiqing1; Bao, Bing-Kun2,3; Mei, Shuhuan1,4; Zhu, Yaohui1; Rui, Yong1,5; Jiang, Shuqiang1,3
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 first propose a probabilistic topic model to discover cuisine-course specific topics. The manilbld 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) multimodal 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.
KeywordCross-region Food Analysis Cuisine Recommendation Cuisine Summarization Culinary Culture Analysis Topic Model
WOS HeadingsScience & Technology ; Technology
Indexed BySCI
Funding OrganizationNational Natural Science Foundation of China(61532018 ; Beijing Municipal Commission of Science and Technology(D161100001816001) ; Beijing Natural Science Foundation(4174106 ; Lenovo Outstanding Young Scientists Program ; National Program for Special Support of Eminent Professionals and National Program for Support of Top-notch Young Professionals ; China Postdoctoral Science Foundation(2016M590135 ; 61602437 ; 4152053) ; 2017T100110) ; 61672497 ; 61572503 ; 61620106003)
WOS Research AreaComputer Science ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Computer Science, Software Engineering ; Telecommunications
WOS IDWOS:000427623000015
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Affiliation1.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
4.Shandong Univ Sci & Technol, Qingdao 266590, Shandong, Peoples R China
5.Lenovo Grp Ltd, Lenovo Corp Res, Beijing 100085, Peoples R China
Recommended Citation
GB/T 7714
Min, Weiqing,Bao, Bing-Kun,Mei, Shuhuan,et al. You Are What You Eat: hxploring Rich Recipe Information for Cross-Region Food Analysis[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2018,20(4):950-964.
APA Min, Weiqing,Bao, Bing-Kun,Mei, Shuhuan,Zhu, Yaohui,Rui, Yong,&Jiang, Shuqiang.(2018).You Are What You Eat: hxploring Rich Recipe Information for Cross-Region Food Analysis.IEEE TRANSACTIONS ON MULTIMEDIA,20(4),950-964.
MLA Min, Weiqing,et al."You Are What You Eat: hxploring Rich Recipe Information for Cross-Region Food Analysis".IEEE TRANSACTIONS ON MULTIMEDIA 20.4(2018):950-964.
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