ComClus: A Self-Grouping Framework for Multi-Network Clustering.

ABSTRACT: Joint clustering of multiple networks has been shown to be more accurate than performing clustering on individual networks separately. This is because multi-network clustering algorithms typically assume there is a common clustering structure shared by all networks, and different networks can provide compatible and complementary information for uncovering this underlying clustering structure. However, this assumption is too strict to hold in many emerging applications, where multiple networks usually have diverse data distributions. More popularly, the networks in consideration belong to different underlying groups. Only networks in the same underlying group share similar clustering structures. Better clustering performance can be achieved by considering such groups differently. As a resul

SUBMITTER: Ni J 

PROVIDER: S-EPMC6221474 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature