Telecommunications Science ›› 2014, Vol. 30 ›› Issue (11): 66-72.doi: 10.3969/j.issn.1000-0801.2014.11.012

• research and development • Previous Articles     Next Articles

Heterogeneous Information Networks Node Similarity Measurement Based on Feature Sub-Graph

Biao Zhang1,2,3,Chuan Li1,2,3,Hongyu Xu1,Yanmei Li1,Ning Yang1,Qian Luo4   

  1. 1 College of Computer Science, Sichuan University, Chengdu 610065, China
    2 National Key Laboratory of Air Control Automation System Technology, Chengdu 610065, China
    3 State Key Laboratory of Software Engineering of Wuhan University, Wuhan 430072, China
    4 The Second Research Institute of CACC, Chengdu 610065, China
  • Online:2014-11-20 Published:2017-07-15

Abstract:

To solve the problem in measuring the similarity of heterogeneous information networks, a similarity measuring algorithm was proposed. It calculates the difference between the maximum common sub-graph and minimum common hyper-graph, based on feature sub-graph of the current node. The algorithm takes graph theory as its foundation, set different weight to different kinds of edges, considers nodes information as well as graph to topological information, and makes full use of the information in heterogeneous network. The result shows that the proposed algorithm has wonderful effectiveness and efficiency.

Key words: heterogeneous information network, graph similarity, similarity measurement, feature sub-graph

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