Multimedia Content Tagging Using Multilabel Decision Tree

This paper formulates the automated tagging of media as a multilabel classification problem. An induction method for creating a multilabel decision tree is presented, then applied to the problem of identifying emotions associated with music clips. The results are compared to two other multilabel classification approaches (CLUS and RAKEL), and the proposed approach is shown to produce better results using a variety of performance measures.