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

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...

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Bibliographic Details
Main Authors: Biao Zhang, Chuan Li, Hongyu Xu, Yanmei Li, Ning Yang, Qian Luo
Format: Article
Language:zho
Published: Beijing Xintong Media Co., Ltd 2014-11-01
Series:Dianxin kexue
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Online Access:http://www.telecomsci.com/zh/article/doi/10.3969/j.issn.1000-0801.2014.11.012/
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Summary: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.
ISSN:1000-0801