berksudan/OTMISC-Topic-Modeling-Tool

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.

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This tool helps researchers and analysts quickly compare how different topic modeling algorithms perform on various text datasets. You input your text data, and it outputs an evaluation of different algorithms, showing which ones best uncover themes in your short or long texts. It's designed for anyone working with text who needs to understand the underlying subjects within their documents.

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Use this if you need to choose the most effective topic modeling method for your specific text data and want to understand the strengths and weaknesses of different algorithms.

Not ideal if you are looking for a ready-to-use, production-grade topic modeling solution without needing to compare or evaluate multiple algorithms.

text-analytics natural-language-processing content-analysis research-evaluation document-categorization
No License Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 6 / 25
Maturity 8 / 25
Community 16 / 25

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Last pushed

May 22, 2025

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