Analyzing short texts infers discriminative and coherent latent topics that is a critical and
fundamental task since many real-world applications require semantic understanding of …

Inferring topics from the overwhelming amount of short texts becomes a critical but
challenging task for many content analysis tasks. Existing methods such as probabilistic …

Nowadays, people use short text to portray their opinions on platforms of social media such
as Twitter, Facebook, and YouTube, as well as on e-commerce websites such as Amazon …

With the explosive growth of short texts on users' interests and preferences, learning
discriminative and coherent latent topics from short texts is a critical and significative work …

Topic models may be a useful tool for locating latent subjects in collections of documents.
Short text clustering has become a more important task as social networking sites like Twitter …

More and more user comments like Tweets are available, which often contain user
concerns. In order to meet the demands of users, a good summary generating from multiple …

Text mining is a new branch of AI that employs natural language processing techniques to
convert unstructured text into a structured format for easier comprehension. It is becoming …

The contents generated from different data sources are usually non-uniform, such as long
texts produced by news websites and short texts produced by social media. Uncovering …

Topic modeling is one of the major concerns in the short texts area, and mining these texts
could uncover meaningful insights. However, the extreme short texts' sparsity and imbalance …

Short text topic modeling attracts many researchers' attention with the emergence of online
social media platforms, such as news websites, Twitter and Facebook. Existing topic models …