Figure 3

Intuitive comparison of MI-GRAAL’s and GHOST’s ASs. Let us assume that we are aligning two graphs \(G_1(V_1,E_1)\) and \(G_2(V_2,E_2).\) Let \(p_1,p_3 \in V_1\), let \(p_2,p_4 \in V_2\), and let the NCF distance (equivalently, similarity) between the node pairs be \(d_1,d_2,d_3,d_4\), as illustrated. MI-GRAAL’s alignment strategy only considers the values \(d_1\) and \(d_2\) when creating an alignment, while GHOST’s AS considers the values \(d_1,d_2,d_3,{\text{and }}d_4\) when doing so.