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自然语言处理领域国内发展态势分析OA

Analysis of the Domestic Development Trend in the Field of Natural Language Processing

中文摘要英文摘要

自然语言处理(NLP)对于理解机器如何与人类语言交互至关重要.通过对 2000-2023 年的文献进行深入分析,结合CiteSpace等文献计量可视化工具,全面探讨了NLP在中国的发展趋势、关键技术和研究热点.研究表明:深度学习、人工智能、机器学习等技术在NLP领域占据核心地位,推动了自然语言理解、生成和解释的进步.知识图谱构建、文本分类、情感分析等研究方向成为研究热点,显示出在信息检索、内容分析等方面的应用潜力.多模态信息融合、自然语言生成的可解释性、跨语言NLP技术,这些方向的探索将为NLP的进一步发展开辟新的道路.

Natural Language Processing(NLP)is essential for understanding how machines interact with human language.Through an in-depth analysis of the literature from 2000 to 2023,combined with bibliometric visualization tools such as CiteSpace,this paper comprehensively discusses the development trend,key technologies and research hotspots of NLP in China.The results show that Deep Learning,Artificial Intelligence,Machine Learning and other technologies occupy the core position in the field of NLP,promoting the progress of natural language understanding,generation and interpretation.Construction of knowledge graph,text classification,sentiment analysis and other research directions have become research hotspots,showing the application potential in information retrieval and content analysis.The exploration of multimodal information fusion,interpretability of natural language generation,and cross-language NLP technology will open up a new path for the further development of NLP.

李惠娇;苏博

山东理工大学 管理学院,山东 淄博 255000

计算机与自动化

自然语言处理发展态势文献计量CiteSpace知识图谱

Natural Language Processingdevelopment trendbiblioitricsCiteSpaceKnowledge Graph

《现代信息科技》 2024 (014)

30-36 / 7

2023年山东理工大学大学生创新创业训练项目

10.19850/j.cnki.2096-4706.2024.14.007

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