title: Robust Multi-Network Clustering via Joint Cross-Domain Cluster Alignment.
abstract: Network clustering is an important problem that has recently drawn a lot of attentions. Most existing work focuses on clustering nodes within a single network. In many applications, however, there existmultiple relatednetworks, in which each network may be constructed from a different domain and instances in one domain may be related to instances in other domains. In this paper, we propose a robust algorithm, MCA, for multi-network clustering that takes into account cross-domain relationships between instances. MCA has several advantages over the existing single network clustering methods. First, it is able to detect associations between clusters from different domains, which, however, is not addressed by any existing methods. Second, it achieves more consistent clustering results on multiple networks by leveraging thedualitybetween clustering individual networks and inferring cross-network cluster alignment. Finally, it provides a multi-network clustering solution that is more robust to noise and errors. We perform extensive experiments on a variety of real and synthetic networks to demonstrate the effectiveness and efficiency of MCA.
authors.affiliation: Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH 44106.
authors.forename: Rui
authors.initials: R
authors.lastname: Liu
authors.affiliation: Department of Computer Science, University of North Carolina at Chapel Hill, NC 27599.
authors.forename: Wei
authors.initials: W
authors.lastname: Cheng
authors.affiliation: School of Computing, Informatics, Decision Systems Engineering, Arizona State University, Tempe, AZ 85281.
authors.forename: Hanghang
authors.initials: H
authors.lastname: Tong
authors.affiliation: Department of Computer Science, University of California, Los Angeles, CA 90095.
authors.forename: Wei
authors.initials: W
authors.lastname: Wang
authors.affiliation: Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH 44106.
authors.forename: Xiang
authors.initials: X
authors.lastname: Zhang