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Information Extraction and Knowledge Map Construction based on Natural Language Processing 基于自然语言处理的信息提取和知识图谱构建
Pub Date : 2024-03-11 DOI: 10.54097/dcc7ba37
Zehan Wang
As a key branch of artificial intelligence, Natural Language Processing (NLP) focuses on making machines understand and generate human language. This paper introduces the basic tasks of NLP, such as lexical analysis, syntactic analysis and semantic understanding, and discusses the cutting-edge technologies such as word embedding. In the aspect of information extraction, this paper deeply discusses the methods of named entity recognition, relationship extraction and event extraction, and points out the challenges in dealing with complex texts. Finally, the paper focuses on the construction of knowledge map, expounds the complete process from data collection to entity identification, relationship extraction, graph construction and query, and emphasizes the core position of graph query in the application of knowledge map. On the whole, this paper provides a comprehensive perspective for understanding NLP, information extraction and knowledge map construction, and points out the importance and future development direction of these technologies in intelligent systems.
作为人工智能的一个重要分支,自然语言处理(NLP)侧重于让机器理解和生成人类语言。本文介绍了 NLP 的基本任务,如词法分析、句法分析和语义理解,并讨论了词嵌入等前沿技术。在信息提取方面,本文深入探讨了命名实体识别、关系提取和事件提取的方法,并指出了处理复杂文本所面临的挑战。最后,本文重点介绍了知识图谱的构建,阐述了从数据收集到实体识别、关系提取、图谱构建和查询的完整过程,并强调了图谱查询在知识图谱应用中的核心地位。总之,本文为理解 NLP、信息提取和知识图谱构建提供了一个全面的视角,并指出了这些技术在智能系统中的重要性和未来的发展方向。
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Frontiers in Computing and Intelligent Systems
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