Comparison of clustering methods in light of paper similarity network topology
10.3969/j.issn.1671-3982.2015.10.008
- VernacularTitle:基于论文相似网络拓扑结构的聚类方法比较
- Author:
Peng HUANG
;
Lei CUI
- Publication Type:Journal Article
- Keywords:
Community structure;
Paper similarity network;
Clustering methods;
Random walk-trap algorithm;
Label propagation algorithm;
BGII algorithm;
Girvan-Newman algorithm;
Igraph
- From:Chinese Journal of Medical Library and Information Science
2015;24(10):33-38
- CountryChina
- Language:Chinese
-
Abstract:
A paper similarity network was constructed in light of semantic similarity algorithm using the complex network processing package , igraph in R language , and analyzed by random walk-trap algorithm , label propagation algorithm, BGII algorithm, and Girvan-Newman algorithm, respectively.The accuracy and stability of these 4 al-gorithms were compared according to the golden standards and the D function for network community classification evaluation index, which showed that the accuracy and stability of random walk-trap algorithm were better than those of the other 3 algorithms and preconditioning of complex network was an important influencing factor for clustering .
