Social and Graph

Social Network and Graph Data Management

Social network is a key Internet service for everyone. The efficient storage, retrieval, processing and analytics of data arising from social network pose great research challenge due to their heterogeneous and complex nature. In particular, many social network data are large graphs, for which efficient processing algorithms are yet to be investigated.

Selected Publications:

  • Q. Zhu, H. Hu, C. Xu, J. Xu, and W. Lee. “Geo-Social Group Queries with Minimum Acquaintance Constraints”, The VLDB Journal, 26(5), 709-727, October 2017 .
  • X. Lin, J. Xu, H. Hu and Z. Fan, “Reducing Uncertainty of Probabilistic Top-k Ranking via Pairwise Crowdsourcing”, IEEE Transactions on Knowledge and Data Engineering (TKDE), 29(10): 2290 – 2303, Oct. 2017.
  • Y. Li, R. Chen, J. Xu, Q. Huang, H. Hu, and B. Choi. “Geo-Social K-Cover Group Queries for Collaborative Spatial Computing.” IEEE Transactions on Knowledge and Data Engineering (TKDE), 27(10):2729 – 2742, October, 2015.
  • Z. Fan, B. Choi, Q. Chen, J. Xu, H. Hu and S. S. Bhowmick. “Structure-Preserving Subgraph Query Services.” IEEE Transactions on Knowledge and Data Engineering (TKDE), 27(08): 2275-2290, August, 2015.
  • Y. Peng, B. Choi, J. Xu, H. Hu, and S. S. Bhowmick. “Side-Effect Estimation: A Filtering Approach to the View Update Problem.” IEEE Transactions on Knowledge and Data Engineering (TKDE), 26(9): 2307 – 2322, August, 2014 .
  • J. Deng, B. Choi, J. Xu, H. Hu, and S. S. Bhowmick. “Incremental Maintenance of the Minimum Bisimulation of Cyclic Graphs.” IEEE Transactions on Knowledge and Data Engineering (TKDE), 25(11): 2536 – 2550, Nov 2013.