Topic models can help to organize and offer insights for us to understand large collections of unstructured text bodies. Originally developed as a text-mining tool, topic models have been used to detect instructive structures in data such as genetic information, images, and networks.
BERTopic is a topic modeling technique that leverages 🤗 transformers and c-TF-IDF to create dense clusters allowing for easily interpretable topics whilst keeping important words in the topic descriptions. BERTopic supports guided, (semi-) supervised, and dynamic topic modeling. It even supports visualizations similar to LDAvis! Corresponding medium posts can be found here and here
first install requirments
pip install -r requirements.txt
streamlit run main.py