Information Extraction and Knowledge Map Construction based on Natural Language Processing

Abstract

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.