Food.com Recipes and Interactions

Shuyang, Li

2019

The Food.com Recipes and Interactions dataset is a large-scale collection of culinary data, comprising over 180,000 recipes and 700,000 user reviews spanning an 18-year period. Compiled by Shuyang Li and published in 2019, this dataset provides a rich source of information for studying user interactions, culinary trends, and recipe recommendation systems. It originates from Food.com (formerly GeniusKitchen), one of the largest online recipe-sharing platforms, making it a valuable resource for researchers and practitioners in food science, natural language processing, and user behavior analysis. The data set is 0.89 GB large and consists of two primary components: recipe data and user interaction data. The recipe data contains structured information about each recipe, including the recipe ID, name tokens (a tokenized version of the recipe title), ingredient tokens, steps tokens (instructions in tokenized form), cooking techniques, caloric level, and ingredient IDs corresponding to specific ingredients. These features allow for deep analysis of how recipes are structured, categorized, and consumed over time. The user interaction data captures engagement metrics, tracking how users interact with recipes. It includes the user ID, a list of recipes reviewed, the number of items reviewed, the ratings assigned, and the total number of ratings provided by each user. This structure enables research into user preference modeling, recipe popularity trends, and the development of personalized recommendation systems for recipe suggestions.