大数据环境下历史人物知识图谱构建与实现  

Design and Implementation of Historical Figures Knowledge Graph Visualization System

作　　者：周亦[1,2] 周明全[1,2] 王学松[1,2] 黄友良[1,2] 

机构地区：[1]北京师范大学信息科学与技术学院,北京100875 [2]教育部虚拟现实应用工程中心,北京100875

出　　处：《系统仿真学报》2016年第10期2560-2566,共7页Journal of System Simulation

摘　　要：大数据时代下,知识图谱和数据可视化技术能够将数据以结构化、可视化的方式呈现,建立以关键词为中心的知识体系,展示数据间相互关系。在此基础上,设计并实现历史人物实体关系可视化系统。系统基于Nodeis平台,采用B/S架构,将繁杂数据分为人物数据和事件数据,分别采用基于标签遍历和基于链接权重的方法进行数据解析、存储至历史人物库。系统提供多种交互方式并具有良好的扩展性和维护性,以丰富直观地形式将历史人物和事件的信息可视化,帮助人们更好理解、梳理及挖掘历史人物及相关事件关系,对相关研究人员有一定的帮助和参考价值。With the advent of big data era, knowledge graph and data visualization technology present the data in a structured, visual way and establish a keyword-oriented knowledge system and render the relationship in a fast and clearly way. In this paper, a historical figures entity relationship visualization system has been established by means of data visualization and knowledge graph. In the system,the complex data are divided into character data and event data by data preprocessing. In the parsing stage, a label traversing method and a method based on weight of links are applied to the divided data respectively. With the layered B/S structure design, the system is based on the Nodejs platform in which a historical figures database is founded. The users can obtain the knowledge graphs of relevant historical figures and events according to distinct needs. This system provides a variety of interactive with good scalability and maintainability and makes contributions to comprehension and exploration of the data and relationship quickly by presenting the data in visual forms. To some extent, it owes reference value to research staff as well.

关 键 词：知识图谱 实体关系 数据解析 数据可视化 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]