dantatartes/tatar_topic_modeling

Topic modeling on Tatar news dataset

This repository includes:

• parser's code for https://tatar-inform.tatar/ website
• Attention-Based Aspect Extraction and LDA models comparison on topic modeling task with collected dataset

Data

You can find the full dataset, word2vec embeddings and model weights in [Download].

Get started

$ pip install -r requirements.txt
$ jupyter notebook

Cite

If you use the code, please consider citing original paper:

@InProceedings{he-EtAl:2017:Long2,
  author    = {He, Ruidan  and  Lee, Wee Sun  and  Ng, Hwee Tou  and  Dahlmeier, Daniel},
  title     = {An Unsupervised Neural Attention Model for Aspect Extraction},
  booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  month     = {July},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics}
}

Aknowledgements

• Attention Based Aspect Extraction implementation from https://github.com/alexeyev/abae-pytorch
• List of Tatar stopwords from https://github.com/aliiae/stopwords-tt