This is the official repo for the IJCAI'22 paper "RecipeRec: A Heterogeneous Graph Learning Model for Recipe Recommendation".
Please first download the data, then put them under folder 'data/'.
For the mappings between the nodes in URI-Graph and the recipe text (recipes_weighted_and_USDAmapped.json) or user ID, please check the following code block:
recipeID2nodeID_dict, nodeID2recipeID_dict = torch.load('../data/recipeID2nodeID_and_nodeID2recipeID.pt')
ingreID2nodeID_dict, nodeID2ingreID_dict = torch.load('../data/ingre2nodeID_and_nodeID2ingre.pt')
userID2userNodeID_dict, userNodeID2userID_dict = torch.load('../data/userID2userNodeID_and_userNodeID2userID.pt')
All codes have been put into a jupyter notebook for easy reading and executing. We further log the results in the notebook for demonstration purposes.
If you find RecipeRec useful, please cite our paper.
@inproceedings{RecipeRec,
author = {Tian, Yijun and Zhang, Chuxu and Guo, Zhichun and Huang, Chao and Metoyer, Ronald and Chawla, Nitesh V.},
title = {RecipeRec: A Heterogeneous Graph Learning Model for Recipe Recommendation},
booktitle = {IJCAI},
year = {2022}
}