Machine learningDeep learning / NLP / CV

Višeslojno modeliranje tema

Višeslojno modeliranje tema otkriva latentnu tematsku strukturu zajedničku za više podatkovnih modaliteta — na primjer, riječi koje se pojavljuju zajedno i slike — učenjem zajedničke probabilističke reprezentacije koja usklađuje teme među modalitetima. Proširuje klasične pristupe koji se temelje isključivo na tekstu, poput LDA, na postavke gdje se svaki dokument ili opažanje sastoji od heterogenih tipova podataka.

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Izvori

  1. Blei, D. M., & Jordan, M. I. (2003). Modeling annotated data. Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 127–134. DOI: 10.1145/860435.860460
  2. Ramage, D., Dumais, S., & Liebling, D. (2010). Characterizing microblogs with topic models. Proceedings of the Fourth International AAAI Conference on Weblogs and Social Media, 130–137. link

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). Multimodal Topic Modeling (Joint Probabilistic Topic Discovery across Multiple Modalities). ScholarGate. https://scholargate.app/hr/deep-learning/multimodal-topic-modeling

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Citirana u

ScholarGateMultimodal Topic Modeling (Multimodal Topic Modeling (Joint Probabilistic Topic Discovery across Multiple Modalities)). Preuzeto 2026-06-15 s https://scholargate.app/hr/deep-learning/multimodal-topic-modeling · Skup podataka: https://doi.org/10.5281/zenodo.20539026