In natural language understanding, there is a hierarchy of lenses through which we can extract meaning - from words to sentences to paragraphs to documents. At the document level, one of the most useful ways to understand text is by analyzing its topics.
tomotopy is a Python extension of tomoto (Topic Modeling Tool) which is a Gibbs-sampling based topic model library written in C++. It utilizes a vectorization of modern CPUs for maximizing speed. The current version of tomoto supports several major topic models including
A. Ferraro, M. Ekstrand, and C. Bauer. Proceedings of the 18th ACM Conference on Recommender Systems, page 884–889. New York, NY, USA, Association for Computing Machinery, (Oct 8, 2024)