An Efficient Algorithm of Star Subgraph Queries on Urban Traffic Knowledge Graph

Author:

Sun Tao,Xu JianqiuORCID,Hu Caiping

Abstract

AbstractKnowledge graph has wide applications in the field of computer science. In the knowledge service environment, the information is large and explosive, and it is difficult to find knowledge of common phenomena. The urban traffic knowledge graph is a knowledge system that formally describes urban traffic concepts, entities and their interrelationships. It has great application potential in application scenarios such as user travel, route planning, and urban planning. This paper first defines the urban traffic knowledge graph and the star subgraph query of the urban traffic knowledge graph. Then, the road network data and trajectory data are collected to extract the urban traffic knowledge, and the urban traffic knowledge graph is constructed with this knowledge. Finally, a star subgraph query algorithm on the urban traffic knowledge graph is proposed. The discussion of the star subgraph query mode gives the corresponding application scenarios of our method in the urban traffic knowledge graph. Experimental results verify the performance advantages of this method.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Computational Mechanics

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Mining Interpretable Regional Co-location Patterns Based on Urban Functional Region Division;Data Science and Engineering;2024-08-29

2. An Unsupervised Learning Framework Combined with Heuristics for the Maximum Minimal Cut Problem;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

3. Representation Learning for Entity Alignment in Knowledge Graph: A Design Space Exploration;2024 IEEE 40th International Conference on Data Engineering (ICDE);2024-05-13

4. Multi- View Teacher with Curriculum Data Fusion for Robust Unsupervised Domain Adaptation;2024 IEEE 40th International Conference on Data Engineering (ICDE);2024-05-13

5. Statistically Inspired Discrepancy Detection for Anomalous Spatio-Temporal Graphs;2024-05-07

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3