Graph pattern matching revised for social network analysis
Wenfei Fan · 2012
Graph pattern matching is fundamental to social network analysis. Traditional techniques are subgraph isomorphism and graph simulation. However, these notions often impose too strong a topological constraint on graphs to find meaningful matches. Worse still, graphs in the real world are typically large, with millions of nodes and billions of edges. It is often prohibitively expensive to compute matches in such graphs. With these comes the need for revising the notions of graph pattern matching and for developing techniques of querying large graphs, to effectively and efficiently identify social communities or groups.