Multi-label text classification (MLTC) is a significant task that aims to assign multiple labels to
each given text. There are usually correlations between the labels in the dataset. However …

In Multi-Label Text Classification (MLTC), one sample can belong to more than one class. It
is observed that most MLTC tasks, there are dependencies or correlations among labels …

In multi-label text classification (MLTC), each given document is associated with a set of
correlated labels. To capture label correlations, previous classifier-chain and sequence-to …

Multi-label text classification (MLTC) aims to tag most relevant labels for the given document.
In this paper, we propose a Label-Specific Attention Network (LSAN) to learn a label-specific …

Abstract Multi-Label Text Classification (MLTC) is one of the most import research of natural
language processing. Although Deep Learning (DL) models have been widely applied to …

Multi-label text classification has been widely concerned by scholars due to its contribution
to practical applications. One of the key challenges in multi-label text classification is how to …

Multi-label text categorization is a type of text categorization, where each document is
assigned to one or more categories. Recently, a series of methods have been developed …

For the multi-label text classification problems with many classes, many existing multi-label
classification algorithms become infeasible or suffer an unaffordable cost. Some researches …

Text multi-label learning deals with examples having multiple labels simultaneously. It can
be applied to many fields, such as text categorization, medical diagnosis recognition and …

Multi-label text classification task is one of the research hotspots in the field of natural
language processing. However, most of the existing multi-label text classification models are …