FuzzyTM: a Software Package for Fuzzy Topic Modeling

Emil Rijcken, Pablo Mosteiro, Kalliopi Zervanou, Marco Spruit, Floortje Scheepers, Uzay Kaymak

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review


Unstructured text data is collected daily in large amounts by many organizations. Analyzing all this data is time intensive and too costly in many cases. One technique to systematically analyze large corpora of texts is topic modeling, which returns the latent topics present in a corpus. Recently, several fuzzy topic modeling algorithms have been proposed and have shown superior results over the existing algorithms. Although various Python libraries offer topic modeling algorithms, none includes fuzzy topic models. Therefore, we present FuzzyTM, a Python library for training fuzzy topic models and creating topic embeddings for downstream tasks. The user-friendly pipelines with default values allow practitioners to train a topic model with minimal effort. Meanwhile, its modular design allows researchers to modify each software element and for future methods to be added.

Original languageEnglish
Title of host publication2022 IEEE International Conference on Fuzzy Systems, FUZZ 2022 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665467100
Publication statusPublished - 2022
Event2022 IEEE International Conference on Fuzzy Systems, FUZZ 2022 - Padua, Italy
Duration: 18 Jul 202223 Jul 2022


Conference2022 IEEE International Conference on Fuzzy Systems, FUZZ 2022


  • Fuzzy Clustering
  • Fuzzy Methods
  • Information Retrieval
  • NLP
  • Topic Modeling
  • Unsupervised Learning


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