Blog - rus

TopicNet: Making Additive Regularisation for Topic Modelling Accessible

Name: TopicNet: Making Additive Regularisation for Topic Modelling Accessible
Journal: Proceedings of The 12th Language Resources and Evaluation Conference
Authors: Victor Bulatov, Evgeny Egorov, Eugenia Veselova, Darya Polyudova, Vasiliy Alekseev, Alexey Goncharov, Konstantin Vorontsov
Abstract:
This paper introduces TopicNet, a new Python module for topic modeling. This package, distributed under the MIT license, focuses on bringing additive regularization topic modelling (ARTM) to non-specialists using a general-purpose high-level language. The module features include powerful model visualization techniques, various training strategies, semi-automated model selection, support for user-defined goal metrics, and a modular approach to topic model training. Source code and documentation are available at https://github.com/machine-intelligence-laboratory/TopicNet
Link: https://www.aclweb.org/anthology/2020.lrec-1.833.pdf
Научные публикации