The idea behind active learning is quite intuitive: instead of annotating a large number of randomly picked instances we carefully select a small number of instances that are maximally informative for the machine learning classifier.
a smaller set of data points is able to boost classifier performance and to yield an accuracy comparable to the one obtained when training the same system on a larger set of randomly chosen data.