ScholarGate
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Machine learningDeep learning / NLP / CV

Word2Vec Debolmente Supervisionato

Word2Vec Debolmente Supervisionato addestra embedding in stile Word2Vec utilizzando etichette generate automaticamente, rumorose o euristiche anziché costose annotazioni manuali. Sfruttando funzioni di etichettatura, supervisione distante o regole basate su parole chiave per assegnare etichette morbide, l'approccio abilita rappresentazioni di parole adattate al dominio anche quando grandi corpora annotati manualmente non sono disponibili.

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Fonti

  1. Mikolov, T., Sutskever, I., Chen, K., Corrado, G., & Dean, J. (2013). Distributed representations of words and phrases and their compositionality. Advances in Neural Information Processing Systems, 26. link
  2. Ratner, A. J., De Sa, C. M., Wu, S., Selsam, D., & Re, C. (2016). Data programming: Creating large training sets, quickly. Advances in Neural Information Processing Systems, 29. link

Come citare questa pagina

ScholarGate. (2026, June 3). Weakly Supervised Word2Vec (Word Embeddings with Weak Supervision). ScholarGate. https://scholargate.app/it/deep-learning/weakly-supervised-word2vec

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ScholarGateWeakly supervised Word2Vec (Weakly Supervised Word2Vec (Word Embeddings with Weak Supervision)). Consultato il 2026-06-15 da https://scholargate.app/it/deep-learning/weakly-supervised-word2vec · Insieme di dati: https://doi.org/10.5281/zenodo.20539026