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Semi-supervised Doc2Vec

Semi-supervised Doc2Vec utvider rammeverket Paragraph Vector av Le og Mikolov (2014) ved å trene tette dokumentinnbygginger (embeddings) på både merkede og umerkede korpus samtidig, ved å bruke tilgjengelige klasselabler som et hjelpesignal for å styre representasjonen mot oppgaverelatert struktur, samtidig som hele den umerkede samlingen utnyttes for generalisering.

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Semi-supervised Doc2Vec
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Kilder

  1. Le, Q. V., & Mikolov, T. (2014). Distributed Representations of Sentences and Documents. Proceedings of the 31st International Conference on Machine Learning (ICML 2014), PMLR 32(2), 1188–1196. link
  2. Word2vec. Wikipedia. link

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ScholarGate. (2026, June 3). Semi-supervised Paragraph Vector (Semi-supervised Doc2Vec). ScholarGate. https://scholargate.app/no/deep-learning/semi-supervised-doc2vec

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ScholarGateSemi-supervised Doc2Vec (Semi-supervised Paragraph Vector (Semi-supervised Doc2Vec)). Hentet 2026-06-15 fra https://scholargate.app/no/deep-learning/semi-supervised-doc2vec · Datasett: https://doi.org/10.5281/zenodo.20539026