We argue that this phenomenon can occur with sequence labeling tasks as well as with classification.
to address this, we propose a new active learning approach called information density (ID): the informativeness of x is weighted by its average similarity to all other sequences in U, subject to a parameter β that controls the relative importance of the density term.