JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2024, Vol. 59 ›› Issue (7): 64-75.doi: 10.6040/j.issn.1671-9352.1.2023.102

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Noise network alignment method integrating multiple features

Ning XIAN1,2(),Yixing FAN1,2,Tao LIAN3,Jiafeng GUO1,2,*()   

  1. 1. Key Laboratory of Network Data Science and Technology, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
    2. School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing 100190, China
    3. College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Jinzhong 030600, Shanxi, China
  • Received:2023-11-24 Online:2024-07-20 Published:2024-07-15
  • Contact: Jiafeng GUO E-mail:xianning21s@ict.ac.cn;guojiafeng@ict.ac.cn

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Abstract:

A multi-round iterative network alignment method is proposed to address the challenges of large structural differences and high noise sensitivity in anchor nodes in network alignment tasks. The method calculates node features of different dimensions using various heuristic approaches at each iteration, utilizing the combination of multiple features to assess the reliability of anchor nodes, filter potential noise, and enhance the confidence of each alignment round. Additionally, a graph neural network is employed to improve the consistency between nodes without attributes, mitigating the impact of structural differences in networks. Experimental results demonstrate that this method achieves high accuracy under high noise conditions, verifying its effectiveness.

Key words: network alignment, graph isomorphism, noise filtering, graphlet

CLC Number: 

  • TP391

Fig.1

Graphlet degree vector"

Table 1

Information of dataset"

数据集 网络名 节点数 边数 节点属性数 所有的对齐节点对数
原始Arenas Email网络 Gs 1 135 5 451 0 1 135
合成Arenas Email网络 Gt 1 135 5 437 0
Facebook Gs 1 043 4 734 0 1 043
Twitter Gt 1 043 4 860 0
Douban Offline Gs 1 118 1 511 538 1 118
Douban Online Gt 3 906 8 164 538

Table 2

Alignment results"

数据集 指标 本文方法/% REGAL/% CENALP/%
Accuracy 94.45 0.09 77.48
Arenas Email Precision@5 98.06 0.44 87.49
Precision@10 98.06 0.88 92.85
Accuracy 96.36 34.13 91.66
Facebook-Twitter Precision@5 97.32 44.87 93.44
Precision@10 98.47 49.09 95.01
Accuracy 46.24 2.77 21.91
Douban Precision@5 63.24 8.50 34.26
Precision@10 72.27 11.09 40.52

Fig.2

Influence of positive anchor nodes ratio on alignment accuracy"

Fig.3

Influence of iterations on alignment accuracy"

Fig.4

Influence of alignment components on alignment accuracy"

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