Customers' reviews and comments are important for businesses to understand users'
sentiment about the products and services. However, this data needs to be analyzed to …

Nowadays, people use online resources such as educational videos and courses. However,
such videos and courses are mostly long and thus, summarizing them will be valuable. The …

This paper focuses on the popular problem of short text clustering. Since the short text
documents typically exhibit high degrees of data sparseness and dimensionality, the …

As redes sociais são utilizadas para expressar opiniões ou interagir com outras pessoas.
Diante do amplo escopo de assuntos publicados e a linguagem informal presente nas …

Understanding the semantic of a collection of texts is a challenging task. Topic models are
probabilistic models that aims at extracting" topics" from a corpus of documents. This task is …

Text mining has become a vital zone that has been attached to some examined ranges such
as computational etymology, data mining, and information recovery (IR). Almost all people …

Text mining has been a vital area that has been linked to some fields of research such as
machine learning, data analysis and gathering, and information recovery. To extract …

Topic modeling and word embedding are commonly used techniques in natural language
processing. However, word embedding lacks discriminating information of homonymy and …

In this study, we uncover the topics of Chinese public cultural activities in 2020 with a two-
step short text clustering (self-taught neural networks and graph-based clustering) and topic …

Topic modeling is a popular technique for learning the thematic structure of large corpora
composed of unlabeled documents, without human supervision. In recent years, various …