Neighborhood based fast graph search in large networks
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Scalable multiple global network alignment for biological data
Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine
A multithreaded algorithm for network alignment via approximate matching
SC '12 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
Message-Passing Algorithms for Sparse Network Alignment
ACM Transactions on Knowledge Discovery from Data (TKDD)
NeMa: fast graph search with label similarity
Proceedings of the VLDB Endowment
Inferring anchor links across multiple heterogeneous social networks
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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We propose a new distributed algorithm for sparse variants of the network alignment problem, which occurs in a variety of data mining areas including systems biology, database matching, and computer vision. Our algorithm uses a belief propagation heuristic and provides near optimal solutions for this NP-hard combinatorial optimization problem. We show that our algorithm is faster and outperforms or ties existing algorithms on synthetic problems, a problem in bioinformatics, and a problem in ontology matching. We also provide a unified framework for studying and comparing all network alignment solvers.