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تسجيل مستخدم جديدMaking Sense of Word Embeddings
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نشر من قبل
Alexander Panchenko
تاريخ النشر
2017
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الهندسة المعلوماتية
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English
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We present a simple yet effective approach for learning word sense embeddings. In contrast to existing techniques, which either directly learn sense representations from corpora or rely on sense inventories from lexical resources, our approach can induce a sense inventory from existing word embeddings via clustering of ego-networks of related words. An integrated WSD mechanism enables labeling of words in context with learned sense vectors, which gives rise to downstream applications. Experiments show that the performance of our method is comparable to state-of-the-art unsupervised WSD systems.
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