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pro vyhledávání: '"Diersen, Isabel"'
Autor:
Basuhi, R., Bhuwalka, Karan, Moore, Elizabeth A., Diersen, Isabel, Malik, Rameen H., Young, Eric, Billy, Romain G., Stoner, Robert, Ceder, Gerbrand, Müller, Daniel B., Roth, Richard, Olivetti, Elsa A.
Publikováno v:
In Joule 20 November 2024 8(11):2960-2973
Topic models are in widespread use in natural language processing and beyond. Here, we propose a new framework for the evaluation of probabilistic topic modeling algorithms based on synthetic corpora containing an unambiguously defined ground truth t
Externí odkaz:
http://arxiv.org/abs/1901.09848
