Abstract: A method for use in generating training data set and in training a learning utility is provided. The method comprising: providing a first set of labeled data and an ensemble of second learning utilities; training the ensemble of second utilities to label data, using the first set of labeled data; providing a second set of unlabeled data; labeling at least one portion of the second set of unlabeled data using the ensemble in order to generate corresponding first labels for said at least one portion of the second set to thereby yield a third set of data pieces corresponding to said at least one portion of the second set and labels thereof; and training the first utility using said third set of data pieces.