Deep learning--based models have surpassed classical machine learning--based
approaches in various text classification tasks, including sentiment analysis, news …

In recent years, there has been an exponential growth in the number of complex documents
and texts that require a deeper understanding of machine learning methods to be able to …

Text classification is the most fundamental and essential task in natural language
processing. The last decade has seen a surge of research in this area due to the …

Text Classification problem has been thoroughly studied in information retrieval problems
and data mining tasks. It is beneficial in multiple tasks including medical diagnose health …

Hierarchical text classification is a challenging subtask of multi-label classification due to its
complex label hierarchy. Existing methods encode text and label hierarchy separately and …

Supervised machine learning studies are gaining more significant recently because of the
availability of the increasing number of the electronic documents from different resources …

Deep learning has exploded in the public consciousness, primarily as predictive and
analytical products suffuse our world, in the form of numerous human-centered smart-world …

Text classification is the most fundamental and essential task in natural language
processing. The last decade has seen a surge of research in this area due to the …

Hierarchical text classification is an important yet challenging task due to the complex
structure of the label hierarchy. Existing methods ignore the semantic relationship between …

Nowadays, with the increasing number of Web 2.0 tools, users generate huge amounts of
data in an enormous and dynamic way. In this regard, the sentiment analysis appeared to be …