2020
EMNLP
EMNLP 2020
Improving Bilingual Lexicon Induction for Low Frequency Words
Abstract
AbstractThis paper designs a Monolingual Lexicon Induction task and observes that two factors accompany the degraded accuracy of bilingual lexicon induction for rare words. First, a diminishing margin between similarities in low frequency regime, and secondly, exacerbated hubness at low frequency. Based on the observation, we further propose two methods to address these two factors, respectively. The larger issue is hubness. Addressing that improves induction accuracy significantly, especially for low-frequency words.
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Interdisciplinary Bridge
— Machine Learning and Natural Language Processing
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Keyword Pioneer
— low frequency word
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Machine Learning > Core Methods > Representation Learning
Machine Learning > Core Methods > Metric Learning
Machine Learning > Core Methods > Embedding Learning
Natural Language Processing > Resources & Methods > Lexical Semantics
Machine Learning > Learning Types > Representation Learning
Natural Language Processing > Resources & Methods > Language Modeling