Google Restaurants
- 1. University of California San Diego
Description
Description
The Google Restaurants dataset is a multi-modal dataset collected by Julian McAuley's lab (University of California San Diego): restaurants from Google Local (Google Maps), including images and reviews posted by users, as well as other metadata for each restaurant. It includes anonymized user IDs, business IDs, ratings, review text, images, geographical location, and business category metadata, available as a subset (30K restaurants, 37K users, 108K reviews, 203K images) or the full dataset (65K restaurants, 1.01M users, 1.77M reviews, 4.43M images).
Please cite the following if you use the data:
Personalized Showcases: Generating Multi-Modal Explanations for Recommendations
An Yan, Zhankui He, Jiacheng Li, Tianyang Zhang, Julian Mcauley
arXiv:2207.00422, 2022
DOI: https://doi.org/10.1145/3539618.3592036
Additional information can be found on GitHub: https://github.com/zzxslp/Gest
Details
| Resource type | Open dataset |
| Title | Google Restaurants |
| Creators |
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| Publisher | University of California San Diego |
| Year of publication | 2022 |
| Research fields | Economics Psychology Sociology Political Science Economic & Social History Communication Sciences Educational Research Other Business Administration |
| Companies | |
| Size | 120 GB |
| Formats | JSON format (.json) GZip Compressed Archive (.gz) |
| External resource | https://cseweb.ucsd.edu/~jmcauley/datasets.html#google_restaurants |
Additional details
Related works
- Is described by
- Conference paper: 10.1145/3539618.3592036 (DOI)
- Is referenced by
- https://github.com/zzxslp/Gest (URL)