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berksudan / OTMISC-Topic-Modeling-Tool

Star 17

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.

visualization natural-language-processing topic-modeling lda unsupervised-learning nmf ctm yahoo-answers 20newsgroup top2vec bertopic lda-bert
  • Updated Aug 26, 2022
  • Jupyter Notebook
active-learning-with-deep-learning-for-nlp

kstrassheim / active-learning-with-deep-learning-for-nlp

Star 6

We present our concept of a new type of Active-Learning for Deep Learning with NLP text classification and experimentally prove its performance against Random Sampling as well as its runtime performance on the Security Threat dataset from CySecAlert. These new Active Learning algorithms are based on Sentence-BERT and BERTopic clustering algorith…

natural-language-processing deep-learning pandas python3 pytorch matplotlib active-learning hdbscan k-means-clustering sentence-bert bertopic
  • Updated Jun 5, 2022
  • Jupyter Notebook

hammadaslam1 / reviews-classifier

Star 4

This is my final year project "customer reviews classification and analysis system using data mining and nlp". It analyzes and then classifies the customer reviews on the basis of their fakeness, sentiments, contexts and topics discussed. The reviews are taken from various e-commerce platforms like daraz and amazon.

sentiment-analysis random-forest fyp topic-modeling lda helpfulness bert final-year-project sentiment-classification context-extraction helpfulness-prediction fake-review-detection bertopic reviews-analysis-nlp reviews-classifier
  • Updated Oct 25, 2024
  • Jupyter Notebook

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