The evolution of topic modeling
R Churchill, L Singh - ACM Computing Surveys, 2022 - dl.acm.org
Topic models have been applied to everything from books to newspapers to social media
posts in an effort to identify the most prevalent themes of a text corpus. We provide an in …
posts in an effort to identify the most prevalent themes of a text corpus. We provide an in …
Topic modeling using latent Dirichlet allocation: A survey
We are not able to deal with a mammoth text corpus without summarizing them into a
relatively small subset. A computational tool is extremely needed to understand such a …
relatively small subset. A computational tool is extremely needed to understand such a …
Effective neural topic modeling with embedding clustering regularization
Topic models have been prevalent for decades with various applications. However, existing
topic models commonly suffer from the notorious topic collapsing: discovered topics …
topic models commonly suffer from the notorious topic collapsing: discovered topics …
Sequence-to-sequence learning with latent neural grammars
Y Kim - Advances in Neural Information Processing …, 2021 - proceedings.neurips.cc
Sequence-to-sequence learning with neural networks has become the de facto standard for
sequence modeling. This approach typically models the local distribution over the next …
sequence modeling. This approach typically models the local distribution over the next …
A survey on neural topic models: methods, applications, and challenges
Topic models have been prevalent for decades to discover latent topics and infer topic
proportions of documents in an unsupervised fashion. They have been widely used in …
proportions of documents in an unsupervised fashion. They have been widely used in …
Branding rhetoric in times of a global pandemic: A text-mining analysis
As the Covid-19 pandemic unfolded, academics and practitioners alike wondered how and
to what extent brands should adapt their advertising and communication efforts to remain …
to what extent brands should adapt their advertising and communication efforts to remain …
Sawtooth factorial topic embeddings guided gamma belief network
Hierarchical topic models such as the gamma belief network (GBN) have delivered
promising results in mining multi-layer document representations and discovering …
promising results in mining multi-layer document representations and discovering …
End-to-end LDA-based automatic weak signal detection in web news
An extremely competitive business environment requires every company to monitor its
competitors and anticipate future opportunities and risks, creating a dire need for competitive …
competitors and anticipate future opportunities and risks, creating a dire need for competitive …
Bayesian progressive deep topic model with knowledge informed textual data coarsening process
Deep topic models have shown an impressive ability to extract multi-layer document latent
representations and discover hierarchical semantically meaningful topics. However, most …
representations and discover hierarchical semantically meaningful topics. However, most …
[HTML][HTML] Exploring public attention in the circular economy through topic modelling with twin hyperparameter optimisation
To advance the circular economy (CE), it is crucial to gain insights into the evolution of
public attention, cognitive pathways related to circular products, and key public concerns. To …
public attention, cognitive pathways related to circular products, and key public concerns. To …