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Flexible Aggregation on Heterogeneous Information Networks

  • Dan YinEmail author
  • Hong Gao
  • Zhaonian Zou
  • Xianmin Liu
  • Jianzhong Li
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9052)

Abstract

With the advent of heterogeneous information networks that consist of multi-type, interconnected nodes, such as bibliographic networks and knowledge graphs, it is important to study flexible aggregation in such networks. In this paper, we investigate the flexible aggregation problem on heterogeneous information networks, which is defined on multi-type of nodes and relations. We develop an efficient heuristic algorithm for aggregation in two phases: informational aggregation and structural aggregation. Extensive experiments on real world data sets demonstrate the effectiveness and efficiency of the proposed algorithm.

Keywords

Node Type Structural Aggregation Aggregation Algorithm Aggregate Function Cite Relation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgement

This work is supported by the National Grand Fundamental Research 973 Program of China under grant 2012CB316200, the Key Program of National Natural Science Foundation of China under grant 60933001, the Major Program of National Natural Science Foundation of China under grant 61190115, the General Program of National Natural Science Foundation of China under grant 61173023.

References

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    Shetty, J., Adibi, J.: Discovering important nodes through graph entropy the case of enron email database. In: Proceedings of the 3rd International Workshop on Link Discovery, pp. 74–81. ACM (2005)Google Scholar
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    Zhao, P., Li, X., Xin, D., Han, J.: Graph cube: on warehousing and olap multidimensional networks. In: Proceedings of the 2011 ACM SIGMOD International Conference on Management of data, pp. 853–864. ACM (2011)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Dan Yin
    • 1
    Email author
  • Hong Gao
    • 1
  • Zhaonian Zou
    • 1
  • Xianmin Liu
    • 1
  • Jianzhong Li
    • 1
  1. 1.Massive Data Computing Research LabHarbin Institute of TechnologyHarbinChina

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