Short text classification is a challenging task in natural language processing. Existing
traditional methods using external knowledge to deal with the sparsity and ambiguity of short …

Due to the advent and increase in the popularity of the Internet, people have been producing
and disseminating textual data in several ways, such as reviews, social media posts, and …

This article studies a new problem of data stream clustering, namely, multiview data stream
(MVStream) clustering. Although many data stream clustering algorithms have been …

Determining the similarity between short texts plays an important role in natural language
processing applications such as search, query suggestion and automatic summary, which …

In multi-label learning, data may simultaneously belong to more than one class. When multi-
label data arrives as a stream, the challenges associated with multi-label learning are joined …

Over the past few decades, short text classification has emerged as a critical downstream
task in natural language processing (NLP). One crucial classification research issue is how …

User interest reflects user preference which plays an important role in commercial decision-
making. Learning and predicting user interest has attracted significant attention in recent …

Real-world applications especially in the fields of social media have produced massive short
text streams. Unlike traditional normal texts, these data present the characteristics of short …

It is key to identify both sentiment and topic for well understanding and managing social
media data such as online reviews and microblogs. This paper studies a robust and reliable …

Due to the popularity of social media and online fora, such as Twitter, Reddit, Facebook, and
Wechat, short text stream clustering has gained significant attention in recent years …