Table of Contents Author Guidelines Submit a Manuscript
Scientific Programming
Volume 2018, Article ID 6749561, 8 pages
https://doi.org/10.1155/2018/6749561
Research Article

Incremental Graph Pattern Matching Algorithm for Big Graph Data

1College of Mathematics and Computer Science, Key Laboratory of High Performance Computing and Stochastic Information Processing, Ministry of Education of China, Hunan Normal University, Changsha 410081, China
2School of Information Science and Engineering, Central South University, Changsha 410083, China

Correspondence should be addressed to Jianliang Gao; nc.ude.usc@gnailnaijoag

Received 19 October 2017; Accepted 20 December 2017; Published 22 January 2018

Academic Editor: Longxiang Gao

Copyright © 2018 Lixia Zhang and Jianliang Gao. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. X. Ren and J. Wang, “Multi-query optimization for subgraph isomorphism search,” Proceedings of the VLDB Endowment, vol. 10, no. 3, pp. 121–132, 2016. View at Publisher · View at Google Scholar
  2. Z. Yang, A. W.-C. Fu, and R. Liu, “Diversified top-k subgraph querying in a large graph,” in Proceedings of the 2016 ACM SIGMOD International Conference on Management of Data, SIGMOD 2016, pp. 1167–1182, USA, July 2016. View at Publisher · View at Google Scholar · View at Scopus
  3. J. Gao, B. Song, W. Ke, and X. Hu, “BalanceAli: Multiple PPI Network Alignment With Balanced High Coverage and Consistency,” IEEE Transactions on NanoBioscience, vol. 16, no. 5, pp. 333–340, 2017. View at Publisher · View at Google Scholar
  4. A. Jentzsch, “Linked Open Data Cloud,” in Linked Enterprise Data, X.media.press, pp. 209–219, Springer Berlin Heidelberg, Berlin, Heidelberg, 2014. View at Publisher · View at Google Scholar
  5. Y. Hao, G. Li, P. Yuan, H. Jin, and X. Ding, “An Association-Oriented Partitioning Approach for Streaming Graph Query,” Scientific Programming, vol. 2017, pp. 1–11, 2017. View at Publisher · View at Google Scholar
  6. W. Fan, J. Li, J. Luo, Z. Tan, X. Wang, and Y. Wu, “Incremental graph pattern matching,” in Proceedings of ACM SIGMOD and 30th PODS 2011 Conference, pp. 925–936, Greece, June 2011. View at Publisher · View at Google Scholar · View at Scopus
  7. W. Fan, C. Hu, and C. Tian, “Incremental Graph Computations,” in Proceedings of ACM International Conference, pp. 155–169, Chicago, Illinois, USA, May 2017. View at Publisher · View at Google Scholar
  8. S. Sun, Y. Wang, W. Liao, and W. Wang, “Mining Maximal Cliques on Dynamic Graphs Efficiently by Local Strategies,” in Proceedings of IEEE 33rd International Conference on Data Engineering (ICDE), pp. 115–118, San Diego, CA, USA, April 2017. View at Publisher · View at Google Scholar
  9. A. Stotz, R. Nagi, and M. Sudit, “Incremental graph matching for situation awareness,” in Proceedings of 12th International Conference on Information Fusion, FUSION 2009, pp. 452–459, usa, July 2009. View at Scopus
  10. C. Wang and L. Chen, “Continuous subgraph pattern search over graph streams,” in Proceedings of the 25th IEEE International Conference on Data Engineering, ICDE 2009, pp. 393–404, China, April 2009. View at Publisher · View at Google Scholar · View at Scopus
  11. S. Choudhury, L. Holder, G. Chin, A. Ray, S. Beus, and J. Feo, “Streamworks - A system for dynamic graph search,” in Proceedings of ACM SIGMOD Conference on Management of Data, SIGMOD 2013, pp. 1101–1104, USA, June 2013. View at Publisher · View at Google Scholar · View at Scopus
  12. K. Semertzidis and E. Pitoura, “Durable Graph Pattern Queries on Historical Graphs,” in Proceedings of International Conference on Data Engineering, pp. 541–552, October 2016.
  13. L. X. Zhang, W. P. Wang, J. L. Gao, and J. X. Wang, “Pattern graph change oriented incremental graph pattern matching,” Journal of Software. Ruanjian Xuebao, vol. 26, no. 11, pp. 2964–2980, 2015. View at Google Scholar · View at MathSciNet
  14. X. Ren and J. Wang, “Exploiting Vertex Relationships in Speeding up Subgraph Isomorphism over Large Graphs,” in Proceedings of the 3rd Workshop on Spatio-Temporal Database Management, Co-located with the 32nd International Conference on Very Large Data Bases, VLDB 2006, pp. 617–628, kor, September 2006. View at Scopus
  15. F. Bi, L. Chang, X. Lin, L. Qin, and W. Zhang, “Efficient subgraph matching by postponing Cartesian products,” in Proceedings of ACM SIGMOD International Conference on Management of Data, pp. 1199–1214, USA, July 2016. View at Publisher · View at Google Scholar · View at Scopus
  16. J. R. Ullmann, “An algorithm for subgraph isomorphism,” Journal of the ACM, vol. 23, no. 1, pp. 31–42, 1976. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  17. W. Fan, J. Li, S. Ma, N. Tang, Y. Wu, and Y. Wu, “Graph pattern matching,” Proceedings of the VLDB Endowment, vol. 3, no. 1-2, pp. 264–275, 2010. View at Publisher · View at Google Scholar
  18. W. Fan, “Graph pattern matching revised for social network analysis,” in Proceedings of the 15th International Conference on Database Theory, ICDT 2012, pp. 8–21, deu, March 2012. View at Publisher · View at Google Scholar · View at Scopus
  19. J. Gao, Q. Ping, and J. Wang, “Resisting re-identification mining on social graph data,” World Wide Web-Internet and Web Information Systems, 2017. View at Publisher · View at Google Scholar
  20. S. Ma, Y. Cao, W. Fan, J. Huai, and T. Wo, “Capturing topology in graph pattern matching,” Proceedings of the VLDB Endowment, vol. 5, no. 4, pp. 310–321, 2011. View at Publisher · View at Google Scholar
  21. A. Fard, M. U. Nisar, L. Ramaswamy, J. A. Miller, and M. Saltz, “A distributed vertex-centric approach for pattern matching in massive graphs,” in Proceedings of IEEE International Conference on Big Data, Big Data 2013, pp. 403–411, USA, October 2013. View at Publisher · View at Google Scholar · View at Scopus
  22. Y. Liang and P. Zhao, “Similarity Search in Graph Databases: A Multi-Layered Indexing Approach,” in Proceedings of IEEE 33rd International Conference on Data Engineering (ICDE), pp. 783–794, San Diego, CA, USA, April 2017. View at Publisher · View at Google Scholar
  23. X. Liu, Y. Liu, H. Song, and A. Liu, “Big Data Orchestration as a Service Network,” IEEE Communications Magazine, vol. 55, no. 9, pp. 94–101, 2017. View at Publisher · View at Google Scholar
  24. J. Gao, J. Wang, J. He, and F. Yan, “Against Signed Graph Deanonymization Attacks on Social Networks,” International Journal of Parallel Programming. View at Publisher · View at Google Scholar
  25. Q. Zhang and A. Liu, “An unequal redundancy level-based mechanism for reliable data collection in wireless sensor networks,” EURASIP Journal on Wireless Communications and Networking, vol. 2016, article 258, 2016. View at Publisher · View at Google Scholar
  26. J. Gao, J. Wang, P. Zhong, and H. Wang, “On Threshold-Free Error Detection for Industrial Wireless Sensor Networks,” IEEE Transactions on Industrial Informatics, pp. 1–11. View at Publisher · View at Google Scholar
  27. Y. Xu, A. Liu, and C. Changqin, “Delay-aware program codes dissemination scheme in internet of everything, mobile information systems,” Mobile Information Systems, vol. 2016, Article ID 2436074, 18 pages, 2016. View at Publisher · View at Google Scholar
  28. X. Liu, S. Zhao, A. Liu, N. Xiong, and A. V. Vasilakos, “Knowledge-aware Proactive Nodes Selection approach for energy management in Internet of Things,” Future Generation Computer Systems, 2017. View at Publisher · View at Google Scholar
  29. K. Zhou, J. Gui, and N. Xiong, “Improving cellular downlink throughput by multi-hop relay-assisted outband D2D communications,” EURASIP Journal on Wireless Communications and Networking, vol. 2017, no. 1, 2017. View at Publisher · View at Google Scholar
  30. Stanford Large Network Dataset Collection, http://snap.stanford.edu/data/index.html.