基于资源传输匹配度的复杂网络链路预测方法

刘树新; 李星; 陈鸿昶; 王凯

doi:10.11959/j.issn.1000-436x.2020124

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基于资源传输匹配度的复杂网络链路预测方法

学术论文 | 更新时间：2024-06-05

- 基于资源传输匹配度的复杂网络链路预测方法
- Link prediction method based on matching degree of resource transmission for complex network
- 通信学报 2020年41卷第6期页码：70-79
- 作者机构：
  
  1. 信息工程大学信息技术研究所，河南郑州 450002
  2. 国家数字交换系统工程技术研究中心，河南郑州 450002
- 作者简介：
  
  [ "刘树新（1987- ），男，山东临朐人，博士，信息工程大学助理研究员，主要研究方向为链路预测、通信网络安全" ]
  [ "李星（1987- ），男，河南新乡人，博士，信息工程大学助理研究员，主要研究方向为链路预测、社团挖掘" ]
  [ "陈鸿昶（1964- ），男，河南郑州人，信息工程大学教授、博士生导师，主要研究方向为通信与信息系统、数据科学与人工智能" ]
  [ "王凯（1980- ），男，河南许昌人，博士，信息工程大学副研究员，主要研究方向为链路预测、社会网络分析" ]
- 基金信息：
  
  国家自然科学基金资助项目(61803384)
- DOI：10.11959/j.issn.1000-436x.2020124
  中图分类号： TP391
- 网络出版日期：2020-06，
  
  纸质出版日期：2020-06-25
- 稿件说明：
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刘树新, 李星, 陈鸿昶, 等. 基于资源传输匹配度的复杂网络链路预测方法[J]. 通信学报, 2020,41(6):70-79.

Shuxin LIU, Xing LI, Hongchang CHEN, et al. Link prediction method based on matching degree of resource transmission for complex network[J]. Journal on communications, 2020, 41(6): 70-79.
刘树新, 李星, 陈鸿昶, 等. 基于资源传输匹配度的复杂网络链路预测方法[J]. 通信学报, 2020,41(6):70-79. DOI： 10.11959/j.issn.1000-436x.2020124.

Shuxin LIU, Xing LI, Hongchang CHEN, et al. Link prediction method based on matching degree of resource transmission for complex network[J]. Journal on communications, 2020, 41(6): 70-79. DOI： 10.11959/j.issn.1000-436x.2020124.

摘要

为了解决基于资源传输的链路预测方法忽略节点间匹配度对资源传输过程影响的问题，提出了一种基于资源传输匹配度的复杂网络链路预测方法。首先，对资源传输路径上的2个端点进行详细分析，提出任意节点间匹配度的量化方法；然后，为了刻画匹配度对于节点间资源传输过程的影响程度，定义了资源传输匹配度；最后，基于资源传输匹配度，考虑节点间双向传输的资源量，提出资源传输匹配度指标。在9个实际网络数据集上的实验测试表明，相比其他基于相似性指标，所提方法在AUC和Precision衡量标准下能够取得更好的效果。

Abstract

In order to solve the problem that many existing resource-transmission-based methods ignore the important influence of the matching degree of two endpoints on resource transmission

a link prediction method was proposed based on matching degree of resource transmission for complex networks.Firstly

by analyzing the two endpoints on the resource transmission path in detail

the method of quantifying the matching degree between two nodes was proposed.Then

in order to describe the influence of matching degree on resource transmission process between nodes

the matching degree of resource transmission was defined.Finally

based on the matching degree of resource transmission

a resource transmission matching index was proposed considering the resource amount of bidirectional transmission between nodes.The experimental results of nine datasets show that compared with other similarity indices

the proposed index can achieve higher prediction accuracy under the AUC and Precision metrics.

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