面向智慧文博的知识图谱构建综述  

Knowledge Graph Construction for Smart Cultural Museums

作　　者：赵卓[1] 田侃[1] 张殊[1] 张晨 吴涛 张浩然 ZHAO Zhuo;TIAN Kan;ZHANG Shu;ZHANG Chen;WU Tao;ZHANG Hao-ran(Department of Cultural Relics Information,Chongqing China Three Gorges Museum,Chongqing 400015,China;School of Cybersecurity and Information Law,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)

机构地区：[1]重庆中国三峡博物馆文物信息部,重庆400015 [2]重庆邮电大学网络空间安全与信息法学院,重庆400065

出　　处：《软件导刊》2022年第5期1-8,共8页Software Guide

基　　金：国家自然科学基金项目(61802039);重庆市自然科学基金项目(cstc2020jcyj-msxmX0804)。

摘　　要：知识图谱是大数据与人工智能交叉融合的一个研究热点,能抽取与表达数据中潜在的知识,进而支撑复杂的推理计算与多样化智能应用的构建。近年来,知识图谱在互联网、金融、医疗保险等领域展开初步应用,然而关于知识图谱与文博领域交叉融合的研究较少。以文化与科技融合创新为背景助力智慧博物馆建设,对当前文博知识图谱构建的背景及必要性进行论述,对近年来相关学者在该研究领域取得的成果进行总结分析,提出文博知识图谱系统的构建框架,阐述知识抽取与关系推理的相关方法与技术,总结基于知识图谱的相关应用以及文博知识图谱运营管理中可能面临的问题,并对文博知识图谱构建面临的挑战以及未来可能的工作方向进行分析与展望。Knowledge graph is a research hotspot in the intersection of big data and artificial intelligence,which can extract and express the potential knowledge in data and support complex reasoning and the construction of diverse intelligent applications.In recent years,there have been initial applications of knowledge graphs in the fields of Internet,finance and medical insurance,however,less attention has been paid to the integration of knowledge graphs with cultural domain.With the integration of culture and technology as the background,help with the construction of the smart museum,discusses the background and necessity of the knowledge graph construction for smart cultural museums,summarizes and analyzes the achievements of relevant scholars in recent years,and gives framework of cultural knowledge graph system.Namely,the related methods and technical schemes of knowledge extraction and relational reasoning are expounded.Then,it summarizes the possible applications and the problems that may be faced in the operation and management of the cultural knowledge graphs.Finally,the challenges and possible works in the future are analyzed and prospected.

关 键 词：知识图谱 文化大数据 智慧博物馆 知识抽取 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]