rel-event
Event recommendation database
Database Description: The Event Recommendation database is obtained from user data on a mobile app called Hangtime. This app allows users to keep track of their friends' social plans. The database contains data on user actions, event metadata, and demographic information, as well as users' social relations, which captures how social relations can affect user behavior. Data is fully anonymized, with no personally identifiable information (such as names or aliases) available.
Database Statistics:
Domain | Social |
Num of Tables | 5 |
Num of Rows | 41,328,337 |
Num of Columns | 128 |
Starting time | 1912-01-01 |
Validation timestamp | 2012-11-21 |
Testing timestamp | 2012-11-29 |
Time window size | 7 days |
Database schema:
To load this relational database in RelBench, do:
from relbench.datasets import get_dataset
dataset = get_dataset("rel-event")
References:
[1] Event Recommendation Engine Challenge.
Dataset License: Open source upon authors agreement.
Node Classification Tasks
user-repeat
Task Description: Predict whether a user will attend an event(by responding yes or maybe) in the next 7 days if they have already attended an event in the last 14 days.
Evaluation metricAUROC
user-ignore
Task Description: Predict whether a user will ignore more than 2 event invitations in the next 7 days
Evaluation metricAUROC
Node Regression Tasks
user-attendance
Task Description: Predict how many events each user will respond yes or maybe in the next seven days.
Evaluation metricMAE