Multi-label classification using labelled association

In this investigation we discuss a multi-label classification problem where documents may have several labels. We put our focus on dependencies among labels in a probabilistic manner, and we extract characteristic features in a form of probabilistic distribution functions by data mining techniques. We show some experimental results, i.e., dependencies among items/labels to see the effectiveness of the approach.