OCTIS: Comparing and Optimizing Topic models is Simple!

1 code implementation • EACL 2021 • Silvia Terragni, Elisabetta Fersini, Bruno Giovanni Galuzzi, Pietro Tropeano, Antonio Candelieri

In this paper, we present OCTIS, a framework for training, analyzing, and comparing Topic Models, whose optimal hyper-parameters are estimated using a Bayesian Optimization approach.

Topic Models