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Machine learningDeep learning / NLP / CV

LDA Emne-model

Latent Dirichlet Allocation (LDA) er en probabilistisk generativ model introduceret af Blei, Ng og Jordan i 2003, som opdager skjult tematisk struktur i store tekstsamlinger ved at repræsentere hvert dokument som en blanding af latente emner (topics) og hvert emne som en sandsynlighedsfordeling over ord i et ordforråd.

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Kilder

  1. Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent Dirichlet Allocation. Journal of Machine Learning Research, 3, 993–1022. link
  2. Latent Dirichlet Allocation. Wikipedia. link

Sådan citerer du denne side

ScholarGate. (2026, June 3). Latent Dirichlet Allocation Topic Model. ScholarGate. https://scholargate.app/da/deep-learning/lda-topic-model

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Refereret af

ScholarGateLDA Topic Model (Latent Dirichlet Allocation Topic Model). Hentet 2026-06-15 fra https://scholargate.app/da/deep-learning/lda-topic-model · Datasæt: https://doi.org/10.5281/zenodo.20539026