基于自然语言处理技术的知识图谱构造方法研究  

Research on Knowledge Graph Construction Methods Based on Natural Language Processing Technology

作　　者：孙伟[1] 李一[1] 马永强[1] SUN Wei;LI Yi;MA Yong-qiang(School of Computer and Big Data,Jining Normal University,Ulanqab,Inner Mongolia 012000)

机构地区：[1]集宁师范学院计算机与大数据学院,内蒙古乌兰察布012000

出　　处：《集宁师范学院学报》2023年第5期94-97,共4页Journal of Jining Normal University

基　　金：集宁师范学院教学改革与研究资助项目“自然语言处理技术在中学语文教学中的应用研究”(JGKT2022011);集宁师范学院科学研究项目“基于深度学习的知识图谱构造研究”(JSKY202216)。

摘　　要：本文基于循环神经网络模型,对内蒙古旅游景点以及游客行为数据进行建模分析,从旅游景点命名实体识别、关系抽取、知识图谱存储与展示三个方面进行量化研究,从而构建统一的可解决模型选择的旅游景点知识图谱模型,为内蒙古旅游知识图谱的构造和旅游景点的个性化推荐提供理论基础,为景点功能区域设计和旅游产业上下游产业融合提供一定的理论参考。This paper,based on the Recurrent Neural Network(RNN)model,conducts modeling and analysis of Inner Mongolia's tourist attractions and tourist behavior data.It quantitatively investigates the construction of a knowledge graph model for tourist attractions,addressing three aspects:named entity recognition of tourist attractions,relationship extraction,and knowledge graph storage and presentation.This research aims to build a unified knowledge graph model for tourist attractions that can solve model selection issues.It provides a theoretical foundation for constructing a knowledge graph of tourism in Inner Mongolia and personalized recommendations for tourist attractions.Additionally,it offers theoretical references for the functional area design of attractions and the integration of the upstream and downstream industries in the tourism sector.

关 键 词：深度学习 自然语言处理 知识图谱 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]