Within the vast expanse of computerized language processing, a revolutionary entity known
as Large Language Models (LLMs) has emerged, wielding immense power in its capacity to …

Multi-label learning is a rapidly growing research area that aims to predict multiple labels
from a single input data point. In the era of big data, tasks involving multi-label classification …

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 …

Abstract Crop Electronic Medical Records (CEMRs) contain a rich diversity of information
about disease characteristics, which is highly valuable as a support to plant doctors …

Prompt-tuning was proposed to bridge the gap between pretraining and downstream tasks,
and it has achieved promising results in Relation Extraction (RE). Although the existing …

In recent years, with the Internet of Things (IoT) and artificial intelligence and the rapid
development of technology, various sports sectors have benefited from technological and …

Multi-label text classification (MLTC) is the process of establishing relationships between
documents and their corresponding labels. Previous research has focused on mining textual …

Tourism knowledge graphs lack cultural content, limiting their usefulness for cultural tourists.
This paper presents the development of a cultural perspective-based knowledge graph …

Time series anomaly detection aims to find specific patterns in time series that do not
conform to general rules, which is one of the important research directions in machine …

文本分类(TC) 是自然语言处理(NLP) 领域的重要基础任务, 多标签文本分类(MLTC) 是TC
的重要分支. 为了对多标签文本分类领域进行深入了解, 介绍了多标签文本分类的概念和流程 …