Abstract
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 language | English |
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Title of host publication | 2022 IEEE International Conference on Fuzzy Systems, FUZZ 2022 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 1-8 |
ISBN (Electronic) | 9781665467100 |
DOIs | |
Publication status | Published - 2022 |
Event | 2022 IEEE International Conference on Fuzzy Systems, FUZZ 2022 - Padua, Italy Duration: 18 Jul 2022 → 23 Jul 2022 |
Conference
Conference | 2022 IEEE International Conference on Fuzzy Systems, FUZZ 2022 |
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Country/Territory | Italy |
City | Padua |
Period | 18/07/22 → 23/07/22 |
Keywords
- Fuzzy Clustering
- Fuzzy Methods
- Information Retrieval
- NLP
- Topic Modeling
- Unsupervised Learning