Link prediction method based on the similarity of high path

Qiuyang GU; Bao WU; Renyong CHI

doi:10.11959/j.issn.1000-436x.2021055

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Link prediction method based on the similarity of high path

Papers | 更新时间：2024-06-05

- Link prediction method based on the similarity of high path
- Journal on Communications Vol. 42, Issue 7, Pages: 61-69(2021)
- 作者机构：
  
  1. 浙江工业大学管理学院，浙江杭州 310023
  2. 浙江工业大学中国中小企业研究院，浙江杭州 310023
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(71173194);The National Social Science Foundation of China(20VYJ073);The National Social Science Foundation of China(17ZDA088);Zhejiang Social Science Planning Key Projects Fundation(20NDJC10Z)
- DOI：10.11959/j.issn.1000-436x.2021055
  CLC： TP391
- Online First：2021-07，
  
  Published：25 July 2021
- 稿件说明：
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Qiuyang GU, Bao WU, Renyong CHI. Link prediction method based on the similarity of high path[J]. Journal on Communications, 2021, 42(7): 61-69.
DOI：

Qiuyang GU, Bao WU, Renyong CHI. Link prediction method based on the similarity of high path[J]. Journal on Communications, 2021, 42(7): 61-69. DOI： 10.11959/j.issn.1000-436x.2021055.

摘要

针对目前链路预测方法普遍存在精度不高、效率低等问题，提出了基于高阶路径相似度的复杂网络链路预测方法。首先，利用路径作为判别特征对复杂网络中的缺失链接进行预测，以实现资源的有效分配，并通过惩罚公共近邻对信息泄露进行限制。其次，将高阶路径作为判别特征，对种子节点对间的可用长路径实施惩罚。最后，利用多个真实复杂网络数据集进行数值算例。实验结果表明，与其他基线方法相比，所提方法具有更优的精度与效率。

Abstract

For the problem that the existing link prediction method has many problems

including low accuracy and low efficiency

a method of high-order path similarity link prediction was proposed.Firstly

the path was used as the judging feature to predict missing links in complex networks

which could make resource allocation more effective and restricts information leakage by punishing public neighbor pairs.Secondly

by using high order paths as judging features

the available long paths between seed nodes would be punished.Finally

several real complex network datasets were used for numerical examples calculation.Experimental results show that the proposed algorithm is more accurate and efficient than other baseline methods.

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references

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