2020
ACL
ACL 2020
Bootstrapping Named Entity Recognition in E-Commerce with Positive Unlabeled Learning
Abstract
AbstractIn this work, we introduce a bootstrapped, iterative NER model that integrates a PU learning algorithm for recognizing named entities in a low-resource setting. Our approach combines dictionary-based labeling with syntactically-informed label expansion to efficiently enrich the seed dictionaries. Experimental results on a dataset of manually annotated e-commerce product descriptions demonstrate the effectiveness of the proposed framework.
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Interdisciplinary Bridge
— Machine Learning and Natural Language Processing
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Keyword Pioneer
— dictionary-based labeling
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Speech & Audio
Authors
Topics
Machine Learning > Learning Types > Weakly Supervised Learning
Natural Language Processing > Understanding > Named Entity Recognition
Natural Language Processing > Applications > Information Extraction
Natural Language Processing > Applications > Named Entity Recognition
Machine Learning > Learning Paradigms > Semi-Supervised Learning