Topic Modelling Meets Deep Neural Networks: A Survey
Abstract
Topic modelling has been a successful technique for text analysis for almost twenty years. When topic modelling met deep neural networks, there emerged a new and increasingly popular research area, neural topic models, with nearly a hundred models developed and a wide range of applications in neural language understanding such as text generation, summarisation and language models. There is a need to summarise research developments and discuss open problems and future directions. In this paper, we provide a focused yet comprehensive overview of neural topic models for interested researchers in the AI community, so as to facilitate them to navigate and innovate in this fast-growing research area. To the best of our knowledge, ours is the first review on this specific topic.
Cite
Text
Zhao et al. "Topic Modelling Meets Deep Neural Networks: A Survey." International Joint Conference on Artificial Intelligence, 2021. doi:10.24963/IJCAI.2021/638Markdown
[Zhao et al. "Topic Modelling Meets Deep Neural Networks: A Survey." International Joint Conference on Artificial Intelligence, 2021.](https://mlanthology.org/ijcai/2021/zhao2021ijcai-topic/) doi:10.24963/IJCAI.2021/638BibTeX
@inproceedings{zhao2021ijcai-topic,
title = {{Topic Modelling Meets Deep Neural Networks: A Survey}},
author = {Zhao, He and Phung, Dinh Q. and Huynh, Viet and Jin, Yuan and Du, Lan and Buntine, Wray L.},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2021},
pages = {4713-4720},
doi = {10.24963/IJCAI.2021/638},
url = {https://mlanthology.org/ijcai/2021/zhao2021ijcai-topic/}
}