Link prediction method based on the similarity of high path

Autor: Qiuyang GU, Bao WU, Renyong CHI
Jazyk: čínština
Rok vydání: 2021
Předmět:
Zdroj: Tongxin xuebao, Vol 42, Pp 61-69 (2021)
Druh dokumentu: article
ISSN: 1000-436X
DOI: 10.11959/j.issn.1000-436x.2021055
Popis: 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.
Databáze: Directory of Open Access Journals