增强基于方面的多重标签与集体学习的伦理物流的伦理物流
Abdulwahab Ali Almazroi1, Nasir Ayub2
1Department of Information Technology, College of Computing and Information Technology at Khulais, University of Jeddah, Jeddah, Saudi Arabia.
PloS one
|May 21, 2024
概括
多标签组合 (MLEn) 通过使用先进的NLP技术准确地提取多标签数据来增强物流通信. 该系统提高了电子商务物流中的效率和伦理语言检测.
科学领域:
- 自然语言处理 (NLP) 是一种自然语言处理.
- 计算语言学 计算语言学
- 数据科学数据科学数据科学
背景情况:
- 有效的沟通对于物流部门的简化运营至关重要.
- 从物流通信中提取多个标签的数据存在重大挑战.
- 现有的方法缺乏对细微物流数据所需的精度和效率.
研究的目的:
- 引入多标签组合 (MLEn) 进行准确的多标签数据提取物流.
- 增强特定于物流通信的文本数据的处理.
- 改善在物流领域的伦理语言检测和情绪分析.
主要方法:
- 使用自然语言工具包 (NLTK) 进行文本预处理.
- 使用情绪强度分析,Word2Vec和Doc2Vec进行特征提取.
- 利用Tf-IDF和Vader进行功能增强和道德内容标签.
主要成果:
- 在不同数据集中,MLEn的准确度达到92%-97%.
- 提出的DenseNet-EHO方法在效率方面比BERT高出8%,其他技术高出15-25%.
- 证明了卓越的精度,回忆,F1得分和计算效率.
结论:
- MLEn为物流中的多标签数据集提供了一个强大的框架.
- 该系统在基于方面的情绪分析中显著提高了精度,多样性和计算效率.
- 丹森网-EHO提供了用于物流通信分析的最先进的解决方案.
相关概念视频
Stereotype Content Model
14.7K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.7K
Labeling Emotion
127
Emotional labeling is a cognitive process that involves identifying and naming one's emotions, such as anger, fear, happiness, or sadness. It allows individuals to recognize and express their internal emotional states, a critical aspect of emotional regulation and communication. Labeling emotions requires more than mere recognition; it also involves drawing upon memory and contextual cues to understand the current situation and apply a corresponding emotional label. For instance, feeling...
127


