An Efficient Active Learning Framework for New Relation Types

@inproceedings{Fu2013AnEA,
  title={An Efficient Active Learning Framework for New Relation Types},
  author={Lisheng Fu and Ralph Grishman},
  booktitle={IJCNLP},
  year={2013}
}
Supervised training of models for semantic relation extraction has yielded good performance, but at substantial cost for the annotation of large training corpora. Active learning strategies can greatly reduce this annotation cost. We present an efficient active learning framework that starts from a better balance between positive and negative samples, and boosts training efficiency by interleaving self-training and co-testing. We also studied the reduction of annotation cost by enforcing… CONTINUE READING

Similar Papers

Loading similar papers…