From f763e4f2e5fccac58a29f1ee0a246e4b14f6b8da Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?M=C3=A1rton=20Kardos?= Date: Sun, 9 Jun 2024 19:04:17 +0200 Subject: [PATCH] Update README.md --- README.md | 23 +++++++++++++++++++++-- 1 file changed, 21 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index c223326..766310c 100644 --- a/README.md +++ b/README.md @@ -14,17 +14,36 @@ **Note**: This package is still work in progress and scientific papers on some of the novel methods (e.g., decomposition-based methods) are currently undergoing peer-review. If you use this package and you encounter any problem, let us know by opening relevant issues. -## Roadmap +## Feature Roadmap - [x] Model Implementation - [x] Pretty Printing - [x] Implement visualization utilites for these models in topicwizard - [x] Thorough documentation - - [x] Dynamic modeling (currently `GMM` and `ClusteringTopicModel` others might follow) + - [x] Dynamic modeling (`GMM`, `ClusteringTopicModel` and `KeyNMF`) - [ ] Publish papers :hourglass_flowing_sand: (in progress..) - [ ] High-level topic descriptions with LLMs. - [ ] Contextualized evaluation metrics. +#### New in version 0.3.0: Dynamic KeyNMF +KeyNMF can now be used for dynamic topic modeling. + +```python +from datetime import datetime +from turftopic import KeyNMF + +corpus: list[str] = [...] +timestamps = list[datetime] = [...] + +model = KeyNMF(10) +doc_topic_matrix = model.fit_transform_dynamic(corpus, timestamps=timestamps, bins=10) + +model.print_topics_over_time() + +# This needs Plotly: pip install plotly +model.plot_topics_over_time() +``` + ## Basics [(Documentation)](https://x-tabdeveloping.github.io/turftopic/) [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/x-tabdeveloping/turftopic/blob/main/examples/basic_example_20newsgroups.ipynb)