文章基本信息

标题：Negative Sampling Improves Hypernymy Extraction Based on Projection Learning
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作者：Dmitry Ustalov ; Nikolay Arefyev ; Chris Biemann 等
期刊名称：Conference on European Chapter of the Association for Computational Linguistics (EACL)
出版年度：2017
卷号：2017
页码：543-550
语种：English
出版社：ACL Anthology
摘要：We present a new approach to extraction of hypernyms based on projection learning and word embeddings. In contrast to classification-based approaches, projection-based methods require no candidate hyponym-hypernym pairs. While it is natural to use both positive and negative training examples in supervised relation extraction, the impact of positive examples on hypernym prediction was not studied so far. In this paper, we show that explicit negative examples used for regularization of the model significantly improve performance compared to the state-of-the-art approach of Fu et al. (2014) on three datasets from different languages.