A computer-implemented method of determining a list of k nodes of a graph that have top-k highest aggregate scores over neighboring nodes within h-hops of said k nodes by using backward processing steps with a partial distribution and forward processing steps, said method comprising:a computer system obtaining a next node u of said graph for said partial distribution on a subset of nodes of said graph for which ƒ(u)≧γ, wherein said ƒ(u) is an initial score of said u, and wherein said γ is a predefined partial distribution threshold;for each node v within h-hops of said u, a processor of said computer system performing said backward processing steps that include determining an upper bound of an aggregate score of said v;said computer system repeating said obtaining said next node and said performing said backward processing until every node of said graph for which ƒ(u)≧γ is obtained as said next node by said obtaining; andsubsequently, said computer system performing said forward processing steps that include:determining an aggregate score of said u by performing an aggregation operation that includes adding an initial score of said u to initial scores of neighboring nodes within h-hops of said u; andif said aggregate score of said u is greater than a lower bound of aggregate scores of said k nodes, then adding said u to said list of k nodes and updating said lower bound of said aggregate scores of said k nodes.
