Querying graph-structured data

被引:0
|
作者
Cheng, Jiefeng [1 ]
Yu, Jeffrey Xu [1 ]
机构
[1] Chinese Univ Hong Kong, Hong Kong, Hong Kong, Peoples R China
关键词
D O I
10.1109/NPC.2007.166
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Graphs have great expressive power to describe the complex relationships among data objects, and there are large graph datasets available such as Web data, semi-structured data and XML data. In this paper we describe our work on querying graph-structured data, including graph labeling methods, reachability joins, and graph pattern matching. We show that we can base on the graph labeling of complex XML and semi-structured data to process path queries and we devise join primitives for matching graph patterns. Novel aspects about using such join primitives for graph pattern matching are addressed.
引用
收藏
页码:23 / 27
页数:5
相关论文
共 50 条
  • [1] Semantic Technologies for Querying Linguistic Annotations: An Experiment Focusing on Graph-Structured Data
    Kouylekov, Milen
    Oepen, Stephan
    [J]. LREC 2014 - NINTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, 2014, : 4331 - 4336
  • [2] Convolutional Kernel Networks for Graph-Structured Data
    Chen, Dexiong
    Jacob, Laurent
    Mairal, Julien
    [J]. 25TH AMERICAS CONFERENCE ON INFORMATION SYSTEMS (AMCIS 2019), 2019,
  • [3] Quantum machine learning of graph-structured data
    Beer, Kerstin
    Khosla, Megha
    Koehler, Julius
    Osborne, Tobias J.
    Zhao, Tianqi
    [J]. PHYSICAL REVIEW A, 2023, 108 (01)
  • [4] Extended Authorization Policy for Graph-Structured Data
    Mohamed A.
    Auer D.
    Hofer D.
    Küng J.
    [J]. SN Computer Science, 2021, 2 (5)
  • [5] Convex Hierarchical Clustering for Graph-Structured Data
    Donnat, Claire
    Holmes, Susan
    [J]. CONFERENCE RECORD OF THE 2019 FIFTY-THIRD ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS, 2019, : 1999 - 2006
  • [6] Convolutional Kernel Networks for Graph-Structured Data
    Chen, Dexiong
    Jacob, Laurent
    Mairal, Julien
    [J]. INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 119, 2020, 119
  • [7] An efficient structural index for graph-structured data
    Fan, Yingjie
    Zhang, Chenghong
    Wang, Shuyun
    Hao, Xiulan
    Hu, Yunfa
    [J]. 7TH IEEE/ACIS INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION SCIENCE IN CONJUNCTION WITH 2ND IEEE/ACIS INTERNATIONAL WORKSHOP ON E-ACTIVITY, PROCEEDINGS, 2008, : 100 - +
  • [8] A Vectorization Approach for Graph-Structured Data to Pattern Recognition
    Sun, Lin
    Chen, Haopeng
    Huang, Feng
    Li, Zhiming
    [J]. 2019 IEEE INTL CONF ON PARALLEL & DISTRIBUTED PROCESSING WITH APPLICATIONS, BIG DATA & CLOUD COMPUTING, SUSTAINABLE COMPUTING & COMMUNICATIONS, SOCIAL COMPUTING & NETWORKING (ISPA/BDCLOUD/SOCIALCOM/SUSTAINCOM 2019), 2019, : 857 - 864
  • [9] Modern Techniques for Querying Graph-Structured Relations: Foundations, System Implementations, and Open Challenges
    Mhedhbi, Amine
    Salihoglu, Semih
    [J]. PROCEEDINGS OF THE VLDB ENDOWMENT, 2022, 15 (12): : 3762 - 3765
  • [10] Preserving the Privacy of Latent Information for Graph-Structured Data
    Shan, Baoling
    Yuan, Xin
    Ni, Wei
    Wang, Xin
    Liu, Ren Ping
    Dutkiewicz, Eryk
    [J]. IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2023, 18 : 5041 - 5055