Link prediction methods based on generalized common neighbor in directed network

Link prediction aims to predict missing or future links through currently observed information of network.Existing mainstream methods are mostly applied to undirected network,and some methods designed for directed network ignored the diverse heterogeneous features of common neighbor.For this problem...

Full description

Saved in:
Bibliographic Details
Main Authors: Xuelei ZHAO, Xinsheng JI, Shuxin LIU, Yu ZHAO
Format: Article
Language:English
Published: POSTS&TELECOM PRESS Co., LTD 2020-10-01
Series:网络与信息安全学报
Subjects:
Online Access:http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2020059
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1841530020631150592
author Xuelei ZHAO
Xinsheng JI
Shuxin LIU
Yu ZHAO
author_facet Xuelei ZHAO
Xinsheng JI
Shuxin LIU
Yu ZHAO
author_sort Xuelei ZHAO
collection DOAJ
description Link prediction aims to predict missing or future links through currently observed information of network.Existing mainstream methods are mostly applied to undirected network,and some methods designed for directed network ignored the diverse heterogeneous features of common neighbor.For this problem,a generalized common neighbor algorithm was proposed.Firstly,a generalized common neighbor was defined for the directed network.Then the degree of contribution of different structures was measured by the joint edge probability of the directed neighbor isomers,and the existing undirected local similarity index is improved by the new definition,redefining eight kinds of directed similarity indicators based on generalized common neighbor.Experiments on 12 datasets show that proposed method generally improves the performance of existing predictive indicators under two metrics.
format Article
id doaj-art-fa8ee165d01044a88ee304e22fe7aadf
institution Kabale University
issn 2096-109X
language English
publishDate 2020-10-01
publisher POSTS&TELECOM PRESS Co., LTD
record_format Article
series 网络与信息安全学报
spelling doaj-art-fa8ee165d01044a88ee304e22fe7aadf2025-01-15T03:14:25ZengPOSTS&TELECOM PRESS Co., LTD网络与信息安全学报2096-109X2020-10-0168910059561017Link prediction methods based on generalized common neighbor in directed networkXuelei ZHAOXinsheng JIShuxin LIUYu ZHAOLink prediction aims to predict missing or future links through currently observed information of network.Existing mainstream methods are mostly applied to undirected network,and some methods designed for directed network ignored the diverse heterogeneous features of common neighbor.For this problem,a generalized common neighbor algorithm was proposed.Firstly,a generalized common neighbor was defined for the directed network.Then the degree of contribution of different structures was measured by the joint edge probability of the directed neighbor isomers,and the existing undirected local similarity index is improved by the new definition,redefining eight kinds of directed similarity indicators based on generalized common neighbor.Experiments on 12 datasets show that proposed method generally improves the performance of existing predictive indicators under two metrics.http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2020059directed networklink predictioncommon neighborheterogeneous fusion
spellingShingle Xuelei ZHAO
Xinsheng JI
Shuxin LIU
Yu ZHAO
Link prediction methods based on generalized common neighbor in directed network
网络与信息安全学报
directed network
link prediction
common neighbor
heterogeneous fusion
title Link prediction methods based on generalized common neighbor in directed network
title_full Link prediction methods based on generalized common neighbor in directed network
title_fullStr Link prediction methods based on generalized common neighbor in directed network
title_full_unstemmed Link prediction methods based on generalized common neighbor in directed network
title_short Link prediction methods based on generalized common neighbor in directed network
title_sort link prediction methods based on generalized common neighbor in directed network
topic directed network
link prediction
common neighbor
heterogeneous fusion
url http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2020059
work_keys_str_mv AT xueleizhao linkpredictionmethodsbasedongeneralizedcommonneighborindirectednetwork
AT xinshengji linkpredictionmethodsbasedongeneralizedcommonneighborindirectednetwork
AT shuxinliu linkpredictionmethodsbasedongeneralizedcommonneighborindirectednetwork
AT yuzhao linkpredictionmethodsbasedongeneralizedcommonneighborindirectednetwork