History-Based Active Learning

In this demo, we will show how Active Learning (AL) can be used to establish and transfer classification information over partially/loosely related datasets, in particular fine-grained user roles on social media, with many and unbalanced classes, large number of data points as well as different internal structures or drifts over time. The key idea is to incorporate the history of learning steps into the tool, allowing us to analyze, restart, and modify the transfer. We also provide a rich visualization that allows the human oracle to interpret the most critical cases.