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Reversing uncertainty sampling to improve active learning schemes
(2015)
Active learning provides promising methods to optimize the cost of manually annotating a dataset. However, practitioners in many areas do not massively resort to such methods because they present technical difficulties and ...
Information extraction with active learning : a case study in legal text
(2015)
Active learning has been successfully applied to a number of NLP tasks. In this paper, we present a study on Information Extraction for natural language licenses that need to be translated to RDF. The final purpose of our ...
Combining semi-supervised and active learning to recognize minority senses in a new corpus
(2015)
In this paper we study the impact of combining active learning with bootstrapping to grow a small annotated corpus from a different, unannotated corpus. The intuition underlying our approach is that bootstrapping includes ...