In recent years, significant progress has been made in text generation. The latest text
generation models are revolutionizing the domain by generating human-like text. It has …

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 …

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 …

Aiming at the problems of low classification accuracy and low efficiency of existing news text
classification methods, a new method of news text classification based on deep learning …

Multi-label learning is an emerging paradigm exploiting samples with rich semantics. As an
effective solution to multi-label learning, the strategy of label-specific features (LIFT) has …

Multi-label learning associates a given data instance with one or several class labels. A
frequent problem with real life multi-label datasets is the lack of complete label information …

The Internet of Things applications are diverse in nature, and a key aspect of it is multimedia
sensors and devices. These IoT multimedia devices form the Internet of Multimedia Things …

Abstract Multi-Label Text Classifiction (MLTC) aims to assign the most relevant labels to
each given text. Existing methods demonstrate that label dependency can help to improve …

With the development of deep learning technology and the disclosure of legal texts, the
classification of legal texts has attracted the attention of researchers. At present, research on …

In text mining problems, text classification is one of the common tasks. Several real-world
document classification involves imbalanced text data. This research investigates the …