Abstract Multi-Label Text Classification (MLTC) is a fundamental and challenging task in
natural language processing. Previous studies mainly focus on learning text representation …

An essential work in natural language processing is the Multi-Label Text Classification
(MLTC). The purpose of the MLTC is to assign multiple labels to each document. Traditional …

Trigger-action platforms are systems that enable users to easily define, in terms of
conditional rules, custom behaviors concerning Internet of Things (IoT) devices and Web …

News media always pursue informing the public at large. It is impossible to overestimate the
significance of understanding the semantics of news coverage. Traditionally, a news text is …

We propose a CNN-BiLSTM-Attention classifier to classify online short messages in Chinese
posted by users on government web portals, so that a message can be directed to one or …

The motivation for this research comes from the gap found in discovering the common
ground for medical context learning through analytics for different purposes of diagnosing …

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 …

In this paper, we focus on the task of multi-label emotion classification and aim to tackle two
problems of this task. First, few studies try to exploit the correlation among different emotions …

The present study analyzed over 26,000 research articles published between 1991 and
2021 in twenty-one major LIS (Library and Information Science) journals, using the machine …

Adapting to dynamic environments is essential for artificial agents, especially those aiming
to communicate with people interactively. In this context, a social robot that adapts its …