Exploring Chinese Dietary Habits Using Recipes Extracted From Websites

• Published in: IEEE access Vol. 7; pp. 24354 - 24361
• Main Authors: Rong, Chuitian, Liu, Zhaopei, Huo, Na, Sun, Huabo
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Apriori; Complexity theory; content-based recommendation; Cooking; Cultural differences; Data mining; Dietary habits; Engines; Entropy; frequent itemset mining; Ingredients; Itemsets; Medical treatment; Recipes; Recommender systems; Websites
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2019.2900504

As more and more cooking recipes are published on the websites by people from different regions, it becomes available to explore the dietary habit of different regions by analyzing their recipes. As a big country owning 32 provinces and autonomous regions, China has generated a series of different cuisines. In this paper, we explore the dietary habits of Chinese by analyzing recipes of different Chinese cuisines. We collected more than 14000 cooking recipes for the 20 different Chinese cuisines from the food-focused website. Our investigation is divided into six perspectives, including the diversity of ingredients, the manifest ingredients, the complexity of cooking, the similarity of dishes, and the dietetic therapy. By the study of recipes with Chinese cuisines, we find strong geographical effects of recipes from different Chinese cuisines. In order to help people understand Chinese habitual collocation of ingredients, we use the Apriori algorithm to find frequent itemsets. Finally, we propose a content-based online recipe recommendation engine to bring some suggestions for people. We believe that our study is helpful to get a deep insight into Chinese dietary culture.