This causes two important problems that motivate our work: 1) annotating data is often a di cult and costly task involving a lot of human work 1 , such that large collections of labelled data are di cult to obtain, and 2) interannotator agreement tends to be low i n e g g enomics collections (Krauthammer et al., 2000), thus calling for methods that are able to deal with noise and incomplete data.
unsupervised techniques do not require labelled data and can thus be applied regardless of the annotation problems.