Music streaming Analytics

Last updated on Nov 20, 2019
Slides

During the course 183.243 Advanced Software Engineering at Vienna University of technology an analytics project for data generated by music streaming royalties was conducted.

The intention was to use anomaly detection to flag unprecedented events, i.e. either platforms having a billing problem or artists gaining too much traction which might indicate fraud.

The project was built using Apache Spark and Spark Jobserver connected via a middleware powered by Apache Camel and a frontend written in Angular JS with Typescript.

anomaly-detection
Alice Wu 吳恩達
Professor of Artificial Intelligence

My research interests include distributed robotics, mobile computing and programmable matter.