On Querying Connected Components in Large Temporal Graphs

Author:

Xie Haoxuan1ORCID,Fang Yixiang1ORCID,Xia Yuyang1ORCID,Luo Wensheng1ORCID,Ma Chenhao1ORCID

Affiliation:

1. The Chinese University of Hong Kong, Shenzhen, Shenzhen, China

Abstract

In this paper, for the first time, we introduce the concepts of window-CCs and window-SCCs on undirected and directed temporal graphs, respectively. We then study the queries of window-CC and window-SCC by developing several efficient index-based query solutions. The space costs of the best indices are linear to the sizes of the temporal graphs. The extensive experimental evaluation on 12 real-world datasets demonstrates the high efficiency and effectiveness of the proposed solutions. In the future, we will develop distributed index construction algorithms, which would be useful for very large temporal graphs containing billions of edges. In the future, we will implement our algorithms by using a distributed computing platform (e.g., Pregel), which would be very useful when the temporal graph is too large to be kept by a single machine.

Funder

Basic and Applied Basic Research Fund in Guangdong Province

Guangdong Talent Program

Publisher

Association for Computing Machinery (ACM)

Cited by 5 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. Evolution Forest Index: Towards Optimal Temporal k -Core Component Search via Time-Topology Isomorphic Computation;Proceedings of the VLDB Endowment;2024-07

2. On Querying Historical Connectivity in Temporal Graphs;Proceedings of the ACM on Management of Data;2024-05-29

3. Share: Stackelberg-Nash based Data Markets;2024 IEEE 40th International Conference on Data Engineering (ICDE);2024-05-13

4. Querying Structural Diversity in Streaming Graphs;Proceedings of the VLDB Endowment;2024-01

5. An Efficient Dynamic Programming Algorithm for Finding Group Steiner Trees in Temporal Graphs;International Journal of Intelligent Systems;2023-11-21

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