Social media platforms such as (Twitter, Facebook, and Weibo) are being increasingly
embraced by individuals, groups, and organizations as a valuable source of information …

Every day the world produces an enormous amount of textual data. This unstructured text is
of little use unless it is labeled using a combination of categories, keywords, tags. Humans …

From statistical to neural models, a wide variety of topic modelling algorithms have been
proposed in the literature. However, because of the diversity of datasets and metrics, there …

Online social media platforms are turning into the prime source of news and narratives about
worldwide events. However, a systematic summarization-based narrative extraction that can …

Recently, some statistic topic modeling approaches, eg, Latent Dirichlet allocation (LDA),
have been widely applied in the field of document classification. However, standard LDA is a …

We investigate two essential challenges in the context of Hierarchical Topic Modeling (HTM)–
(i) the impact of data representation and (ii) topic evaluation. The data representation directly …

Recently, some statistical topic modeling approaches based on LDA have been applied in
the field of supervised document classification, where the model generation procedure …

Convolutional neural networks, recurrent neural networks, and transformers have excelled
in representation learning for large-scale multi-label text classification. However, there have …

Recently, some statistical topic modeling approaches have been widely applied in the field
of supervised document classification. However, there are few researches on these …

During the production of an animated film, professionals at the animation studio prepare
thousands of notes. These notes describe improvements and corrections identified by …