We have extended the averaged perceptron setup in the following way: the training algorithm is fed, in each iteration, by a concatenation of the supervised data (the manually tagged corpus) and the automatically pre-tagged unsupervised data, different for each iteration (in this order).
the training algorithm proper does not change at all: it is the data and their selection (including the selection of the way they are automatically tagged) that makes all the difference.