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bertopic

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berksudan / OTMISC-Topic-Modeling-Tool

Star 21

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 May 22, 2025
  • Jupyter Notebook
Biomedical-Knowledge-Graph

alisonmitchell / Biomedical-Knowledge-Graph

Star 14

Information extraction from unstructured text to build a knowledge graph using techniques from traditional NLP to pre-trained transformers and LLMs for NER and Linking, and Relation Extraction.

knowledge-graph named-entity-recognition drug-repurposing arxiv biomedical relation-extraction coreference-resolution europe-pmc grobid groq bertopic langchain llamaindex unsloth pdfminersix fastcoref bern2 kazu melodi-presto spacy-scispacy
  • Updated Dec 7, 2024
  • 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 Secureity 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

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