Comparison of clustering methods in light of paper similarity network topology / 中华医学图书情报杂志

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 .