阿拉伯情绪分析的进步和挑战:十年的方法,应用和资源开发
Amani A Aladeemy1,2, Ali Alzahrani3, Mohammad H Algarni4
1Dept. of Computer Science & Information Technology, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, India.
Heliyon
|November 18, 2024
概括
本综述强调了阿拉伯情绪分析 (ASA) 面临的挑战,原因是语言复杂性和资源短缺. 开发新的词典和数据集对于在各个领域准确的ASA至关重要.
科学领域:
- 自然语言处理自然语言处理.
- 计算语言学 计算语言学
- 人工智能的人工智能
背景情况:
- 数字内容的扩散需要强大的情绪分析 (SA).
- 阿拉伯语言情绪分析 (ASA) 识别了阿拉伯文文本中的情绪 (积极,消极,中立).
- 现有的ASA方法由于语言复杂性和资源限制而面临挑战.
研究的目的:
- 在过去十年中对阿拉伯情绪分析进行全面审查.
- 在当前的ASA方法,词典和数据集中识别差距和局限性.
- 为研究人员提供有关ASA可访问资源和技术的见解.
主要方法:
- 在过去10年中发表的150篇论文的系统文献综述.
- 在主要的学术数据库中进行的搜索:谷歌学者,Scopus和科学网.
- 包括标准集中在ASA研究上,不包括较旧的出版物.
主要成果:
- 在ASA的重大挑战源于阿拉伯语独特的语言特征,多种方言和形态变异.
- 严重缺乏注释数据集,全面的词典和专门的编程工具阻碍了ASA的开发.
- 没有一个单一的公共词典能够有效地支持电子商务,政治和公共卫生等多个领域的ASA.
结论:
- 进一步开发资源,包括方言特定的阿拉伯情感词典,至关重要.
- 解决注释数据集和预处理工具的稀缺性对于推进ASA至关重要.
- 未来的研究应该专注于创建标准化,适应领域的资源,以提高ASA准确性.
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