命名实体识别的演变和新兴趋势:从2000年到2023年的图书法分析分析
Jun Yang1, Taihua Zhang1,2, Chieh-Yuan Tsai3
1School of Mechanical and Electrical Engineering, Guizhou Normal University, Guiyang, Guizhou, 550025, China.
Heliyon
|May 6, 2024
概括
本文献计量研究使用1300份文件审查了命名实体识别 (NER) 的进展情况. 它确定了关键的研究前沿和热点,以指导本文本挖掘技术的未来进展.
科学领域:
- 计算机科学 计算机科学
- 信息科学 信息科学 信息科学
- 自然语言处理自然语言处理.
背景情况:
- 从自然语言文本中提取信息是一项挑战.
- 命名实体识别 (NER) 是文本数据处理和挖掘的关键技术.
- NER已经成为一个重要的研究领域.
研究的目的:
- 提供关于命名实体认可 (NER) 进展的准确和客观审查.
- 确定NER领域的研究前沿,发展轨道和热点.
- 为研究人员提供洞察力,以掌握相关信息并促进NER发展.
主要方法:
- 从科学网络数据库中对1300个与NER相关的文件进行了图书统计分析.
- 使用CiteSpace软件进行数据分析和可视化.
- 审查了出版物发行,核心作者,国际发展和机构贡献.
主要成果:
- 在NER中确定了五个关键的研究前沿和七个突出的研究热点.
- 分析了NER文献和期刊的分布特征.
- 绘制了NER研究中核心作者,国家和机构的协作网络.
结论:
- 在NER研究中,在宏观和微观层面都有明显的进展.
- 该研究提供了对NER现状和未来方向的全面概述.
- 结果为NER领域的研究人员和机构提供了有价值的指导.
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