Content recommendation is at the heart of most subscription-based media stream platforms. A good recommendation system can vastly enhance user experience and increase user engagement. On the other hand, predicting user churn is a common challenge facing all subscription-based platforms. Predicting user churn and understanding the key factors leading to membership renewal have great business value.
We invite you to take part in one of the following shared tasks:
In this task, the participants are requested to exploit the provided user history
and music metadata to develop a recommendation system. Given a copy of user listening history during
a two month period, participants are required to predict what songs a set of predetermined users
would listen to during the next month.
Kaggle: https://www.kaggle.com/c/kkbox-music-recommendation-challenge
In this task, we would like to know whether a user will renew his/her subscription
within 30 days after the current subscription expires.
Kaggle: https://www.kaggle.com/c/kkbox-churn-prediction-challenge
Learn more at: https://wsdm-cup-2018.kkbox.events/
All deadlines are 11:59 PM, Pacific Standard Time (PST).