In this paper, we propose a highly robust point-matching method (Graph Transformation Matching - GTM) relying on finding the consensus graph emerging from putative matches. Such m...
Our world today is generating huge amounts of graph data such as social networks, biological networks, and the semantic web. Many of these real-world graphs are edge-labeled graph...
Ruoming Jin, Hui Hong, Haixun Wang, Ning Ruan, Yan...
One fundamental challenge for mining recurring subgraphs from semi-structured data sets is the overwhelming abundance of such patterns. In large graph databases, the total number ...
Given a distribution of pebbles on the vertices of a graph G, a pebbling move takes two pebbles from one vertex and puts one on a neighboring vertex. The pebbling number (G) is th...
David P. Bunde, Erin W. Chambers, Daniel W. Cranst...
We propose a manifold learning approach to fiber tract clustering using a novel similarity measure between fiber tracts constructed from dual-rooted graphs. In particular, to gene...
Andy Tsai, Carl-Fredrik Westin, Alfred O. Hero, Al...