TopMost
OCTIS
| TopMost | OCTIS | |
|---|---|---|
| 1 | 7 | |
| 146 | 688 | |
| - | 1.5% | |
| 7.6 | 6.0 | |
| about 2 months ago | 5 months ago | |
| Jupyter Notebook | Python | |
| Apache License 2.0 | MIT License |
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TopMost
OCTIS
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Interpretation of topic modeling results between LDA and BERTopic
OCTIS
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(NLP) Best practices for topic modeling and generating interesting topics?
My team and I have recently released a python library called OCTIS (https://github.com/mind-Lab/octis) that allows you to automatically optimize the hyperparameters of a topic model according to a given evaluation metric (not log-likelihood). I guess, in your case, you might be interested in topic coherence. So you will get good quality topics with a low effort on the choice of the hyperparameters. Also, we included some state-of-the-art topic models, e.g. contextualized topic models (https://github.com/MilaNLProc/contextualized-topic-models).
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I am working on a topic modelling paper and I need your help
I recently released a topic modeling library that also includes different evaluation measures. If you are interested, I leave here the link: https://github.com/mind-Lab/octis
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Latest trends in topic modelling?
Silvia Terragni (a coauthor on the above) also brought a topic modelling library OCTIS which was exhibited as a demo paper and aims to be the huggingface transformers of topic modelling - it includes wrappers around the above model as well as and LDA and some baselines as well as some tools and frameworks for comparing them.
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OCTIS a python framework to compare and optimize Topic Models
Link to the code Paper
- OCTIS, our new python framework to optimize and compare topic models has been accepted at EACL2021!
- [p] OCTIS: Optimizing and Comparing Topic models Is Simple. Our new python framework to compare and optimize topic models using Bayesian Optimization
What are some alternatives?
tf-transformers - State of the art faster Transformer with Tensorflow 2.0 ( NLP, Computer Vision, Audio ).
BERTopic - Leveraging BERT and c-TF-IDF to create easily interpretable topics.
converse - Conversational text Analysis using various NLP techniques
contextualized-topic-models - A python package to run contextualized topic modeling. CTMs combine contextualized embeddings (e.g., BERT) with topic models to get coherent topics. Published at EACL and ACL 2021 (Bianchi et al.).
auto-sklearn - Automated Machine Learning with scikit-learn
medspacy - Library for clinical NLP with spaCy.
image-similarity-measures - :chart_with_upwards_trend: Implementation of eight evaluation metrics to access the similarity between two images. The eight metrics are as follows: RMSE, PSNR, SSIM, ISSM, FSIM, SRE, SAM, and UIQ.
rakun2 - RaKUn 2.0 - A fast keyword detection algorithm
SMAC3 - SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
CodeSearchNet - Datasets, tools, and benchmarks for representation learning of code.