2017
ACL
ACL 2017
Self-Crowdsourcing Training for Relation Extraction
Abstract
AbstractIn this paper we introduce a self-training strategy for crowdsourcing. The training examples are automatically selected to train the crowd workers. Our experimental results show an impact of 5% Improvement in terms of F1 for relation extraction task, compared to the method based on distant supervision.
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Interdisciplinary Bridge
- Machine Learning and Natural Language Processing
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Trend Setter
- Information Extraction
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Keyword Pioneer
- worker training
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Cross-Pollinator
- Artificial Intelligence, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Knowledge & Reasoning, Machine Learning, Natural Language Processing, Speech & Audio
Authors
Topics
Machine Learning > Learning Types > Active Learning
Machine Learning > Learning Types > Self-Supervised Learning
Machine Learning > Learning Types > Semi-Supervised Learning
Natural Language Processing > Applications > Information Extraction
Natural Language Processing > Applications > Relation Extraction