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We created a topic modeling pipeline to evaluate different topic modeling algorithms, including their performance on short and long text, preprocessed and not preprocessed datasets, and with different embedding models. Finally, we summarized the results and suggested how to choose algorithms based on the task.

Shell 0.01% Jupyter Notebook 99.81% Python 0.19%
20newsgroup bertopic ctm lda nmf top2vec topic-modeling unsupervised-learning yahoo-answers natural-language-processing

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