Validation of scientific topic models using graph analysis and corpus metadata
MA Vázquez, J Pereira-Delgado, J Cid-Sueiro… - Scientometrics, 2022 - Springer
Probabilistic topic modeling algorithms like Latent Dirichlet Allocation (LDA) have become
powerful tools for the analysis of large collections of documents (such as papers, projects, or
funding applications) in science, technology an innovation (STI) policy design and
monitoring. However, selecting an appropriate and stable topic model for a specific
application (by adjusting the hyperparameters of the algorithm) is not a trivial problem.
Common validation metrics like coherence or perplexity, which are focused on the quality of …
powerful tools for the analysis of large collections of documents (such as papers, projects, or
funding applications) in science, technology an innovation (STI) policy design and
monitoring. However, selecting an appropriate and stable topic model for a specific
application (by adjusting the hyperparameters of the algorithm) is not a trivial problem.
Common validation metrics like coherence or perplexity, which are focused on the quality of …
Validation of scientific topic models using graph analysis and corpus metadata
MA Vázquez López, J Pereira Delgado, J Cid Sueiro… - 2022 - e-archivo.uc3m.es
Probabilistic topic modeling algorithms like Latent Dirichlet Allocation (LDA) have become
powerful tools for the analysis of large collections of documents (such as papers, projects, or
funding applications) in science, technology an innovation (STI) policy design and
monitoring. However, selecting an appropriate and stable topic model for a specific
application (by adjusting the hyperparameters of the algorithm) is not a trivial problem.
Common validation metrics like coherence or perplexity, which are focused on the quality of …
powerful tools for the analysis of large collections of documents (such as papers, projects, or
funding applications) in science, technology an innovation (STI) policy design and
monitoring. However, selecting an appropriate and stable topic model for a specific
application (by adjusting the hyperparameters of the algorithm) is not a trivial problem.
Common validation metrics like coherence or perplexity, which are focused on the quality of …
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