Vertex nomination via seeded graph matching
Abstract
Consider two networks on overlapping, nonidentical vertex sets. Given vertices of interest (VOIs) in the first network, we seek to identify the corresponding vertices, if any exist, in the second network. While in moderately sized networks graph matching methods can be applied directly to recover the missing correspondences, herein we present a principled methodology appropriate for situations in which the networks are too large/noisy for brute‐force graph matching. Our methodology identifies vertices in a local neighborhood of the VOIs in the first network that have verifiable corresponding vertices in the second network. Leveraging these known correspondences, referred to as seeds, we match the induced subgraphs in each network generated by the neighborhoods of these verified seeds, and rank the vertices of the second network in terms of the most likely matches to the original VOIs. We demonstrate the applicability of our methodology through simulations and real data examples.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Mar 16, 2020
- Source ID
- 10.1002/sam.11454
Entities
People
- Carey E. Priebe
- Heather Gaddy Patsolic
- Vince Lyzinski
- Youngser Park
Organizations
- Air Force Research Laboratory
- Defense Advanced Research Projects Agency
- Engineering and Physical Sciences Research Council
- Johns Hopkins University
- University of Maryland