Music recommendation system
Introduction
In this task, you will be asked to predict the chances of a user listening to a song repetitively after the first observable listening event within a time window was triggered. If there are recurring listening event(s) triggered within a month after the user¡¯s very first observable listening event, its target is marked 1, and 0 otherwise in the training set. The same rule applies to the testing set.
KKBOX provides a training data set consists of information of the first observable listening event for each unique user-song pair within a specific time duration. Metadata of each unique user and song pair is also provided. The use of public data to increase the level of accuracy of your prediction is encouraged.
Data description
https://www.kaggle.com/c/kkbox-music-recommendation-challenge/data
Requirements
1. You need to submit a pdf format report, in which you should clearly describe the method and explain the result.
2. The code should be uploaded to Github and the Github link should be provided in the report.
Contact TA
Xiao Jiashun (jxiaoae@connect.ust.hk)