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تسجيل مستخدم جديدNegative Sampling Improves Hypernymy Extraction Based on Projection Learning
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Alexander Panchenko
تاريخ النشر
2017
مجال البحث
الهندسة المعلوماتية
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English
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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 negative 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.
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