Joint coordinate attention mechanism and instance normalization for COVID online comments text classification.

ABSTRACT:

Background

The majority of extant methodologies for text classification prioritize the extraction of feature representations from texts with high degrees of distinction, a process that may result in computational inefficiencies. To address this limitation, the current study proposes a novel approach by directly leveraging label information to construct text representations. This integration aims to optimize the use of label data alongside textual content.

Methods

The methodology initiated with separate pre-processing of texts and labels, followed by encoding through a projection layer. This research then utilized a conventional self-attention model enhanced by instance normalization (IN) and Gaussian Error Linear Unit (GELU) functions to assess emotional valences in review t

SUBMITTER: Zhu R 

PROVIDER: S-EPMC11419621 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature