The goal finding rate can be better understood by analyzing the nodes selected at each iteration step. We characterize each node by its minimum path length to the goal node. Each node is outlined as the number of reaction paths included in the reaction pathway that has the minimum number of reaction paths among all the possible reaction pathways from each node to the goal node, only composed of reaction paths under the constraint τ max (note that this characterization is possible because we can access the detailed information of the underlying reaction path network in the database, and that this analysis aims at unveiling the origin of the goal finding performance dependent on the selection policies, and in actual applications no one can access the reaction path network a priori). Figure shows the fractions of nodes selected in each iteration step when applying the structural-similarity-based search to the Passerini reaction data, as classified by the minimal path lengths to the goal node.