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

Biao Zhang; Chuan Li; Hongyu Xu; Yanmei Li; Ning Yang; Qian Luo

doi:10.3969/j.issn.1000-0801.2014.11.012

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

research and development | 更新时间：2024-06-05

- Heterogeneous Information Networks Node Similarity Measurement Based on Feature Sub-Graph
- DIANXIN KEXUE Vol. 30, Issue 11, Pages: 66-72(2014)
- 作者机构：
  
  1. 四川大学计算机学院成都 610065
  2. 国家空管自动化系统技术重点实验室成都 610065
  3. 武汉大学软件工程国家重点实验室武汉 430072
  4. 中国民用航空总局第二研究所成都 610065
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.1000-0801.2014.11.012
  CLC：
- Published Online：2014-11，
  
  Published：20 November 2014
- 稿件说明：
移动端阅览
Biao Zhang, Chuan Li, Hongyu Xu, et al. Heterogeneous Information Networks Node Similarity Measurement Based on Feature Sub-Graph[J]. Dianxin kexue, 2014, 30(11): 66-72.
DOI：

Biao Zhang, Chuan Li, Hongyu Xu, et al. Heterogeneous Information Networks Node Similarity Measurement Based on Feature Sub-Graph[J]. Dianxin kexue, 2014, 30(11): 66-72. DOI： 10.3969/j.issn.1000-0801.2014.11.012.

摘要

摘要：为解决异构信息网络相似性度量的问题，提出了基于节点特征子图的节点相似性度量算法，通过节点特征子图的最大公共子图与最小公共超图之间的差异性，进行节点间的相似性度量。该算法以图理论为基础，根据连边的不同类型设定不同权值，在考虑节点信息相似的同时，加入节点在网络中的结构信息，最大程度地利用了异构信息网络所富含的信息。实验结果表明，提出的算法具有较好的性能和有效性。

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.

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references

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