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Rudarenje naučnih tekstova — Akademska obrada prirodnog jezika

Rudarenje naučnih tekstova je postupak obrade prirodnog jezika primenjen na akademsku literaturu. Zasnovano na domen-specifičnim pred-obučenim modelima kao što su SciBERT (Beltagy et al., 2019) i SPECTER (Cohan et al., 2020), automatski izdvaja hipoteze, metodologije, nalaze i akademske doprinose iz celovitih radova ili apstrakata, omogućavajući automatizaciju sistematskog pregleda, analizu istraživačkih trendova i mapiranje nauke u velikom obimu.

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Izvori

  1. Beltagy, I., Lo, K., & Cohan, A. (2019). SciBERT: A Pretrained Language Model for Scientific Text. EMNLP 2019. link
  2. Cohan, A., Feldman, S., Beltagy, I., Downey, D., & Weld, D. (2020). SPECTER: Document-Level Representation Learning using Citation-Informed Transformers. ACL 2020. link

Kako citirati ovu stranicu

ScholarGate. (2026, June 1). Scientific Text Mining (Scholarly NLP). ScholarGate. https://scholargate.app/sr/text-mining/scientific-text-mining

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Citirana u

ScholarGateScientific Text Mining (Scientific Text Mining (Scholarly NLP)). Preuzeto 2026-06-15 sa https://scholargate.app/sr/text-mining/scientific-text-mining · Skup podataka: https://doi.org/10.5281/zenodo.20539026