Leveraging BERT and c-TF-IDF to create easily interpretable topics.

Top2Vec learns jointly embedded topic, document and word vectors.

Interface for easier topic modelling.

GPU-Powered Topic Modelling

Topic-Specific Diagnostics for LDA and CTM Topic Models

NLP Section of the Data Science course, NRU HSE

Small tutorial on how you can use BERT for Topic Modeling

Implementation and helper scripts for the BART-TL model - https://www.aclweb.org/anthology/2021.eacl-main.121/

A set of methods for finding an appropriate number of topics in a text collection

Multimodal and multilingual topic model with pretrained embeddings

Topic Modelling to segregate news report data to different topics using Gensim, NLTK, Spacy.

The project provides insights for business owners to improve their businesses and recommendations for users to improve their experience with the application

Multilingual topic labelling of news topics

An automated topic modelling system that outputs into a Shiny App

I don't feel like reading this research paper that my professor has us doing so I made this summarizer using Latent Dirichlet Allocation

A Machine Learning NLP project to extract research topics based on publication titles using KeyBERT unsupervised keyword extraction approach.

Topic Modelling & Sentiment Analysis of Data Science Subreddit

TOMMY is een topic modelling applicatie die ontwikkeld is door studenten van de Universiteit Utrecht in opdracht van EMMA. Voor het uitvoeren van topic modelling wordt het achterliggende Latent Dirichlet Allocation (LDA) algoritme of Non-Negative Matrix Factorization (NMF) algoritme uitgevoerd op de door de gebruiker aangeleverde bestanden.

Analysis of social media conversations surrounding COVID-19 in Singapore

My published paper on the application of LDA on documents. Base corpus: Thousands of LDS General Conference articles spanning decades.