Topic Modelling Meets Deep Neural Networks: A Survey
It addresses the need for a focused overview of neural topic models for AI researchers, but it is incremental as it reviews existing work without introducing new methods.
This paper provides a comprehensive survey of neural topic models, summarizing over a hundred models developed for text analysis and applications like text generation and summarization, to help researchers navigate and innovate in this fast-growing area.
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 over 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 focusing on this specific topic.