1. A method, in a data processing system comprising a processor and a memory, for performing a cognitive operation, the method comprising: receiving, by the data processing system, an input graph comprising a plurality of first nodes, where subsets of first nodes in the plurality of first nodes are coupled to one another via one or more first edges and each first edge in the one or more first edges has an associated weight value; generating, by the data processing system, a blinking graph model based on the graph, wherein the blinking graph model comprises blink rate values associated with second edges of the blinking graph model calculated based on weights of corresponding first edges in the input graph, wherein the blink rate value specifies a fraction of time a corresponding second edge is determined to be present in the blinking graph model; receiving, by the data processing system, a request for performance of a cognitive operation, wherein the request comprises an identification of a node of interest, calculating, by the data processing system, a relatedness metric for a target node in the blinking graph model relative to the node of interest based on the blink rate values of the second edges, wherein the relatedness metric indicates a degree of relatedness of the target node to the node of interest, wherein calculating the relatedness metric for the target node comprises calculating the relatedness metric for each path from the node of interest to a plurality of target nodes in the blinking graph model; and performing, by the data processing system, a cognitive operation based on the relatedness metric.
1. A method, in a data processing system comprising a processor and a memory, for performing a cognitive operation, the method comprising: receiving, by the data processing system, an input graph comprising a plurality of first nodes, where subsets of first nodes in the plurality of first nodes are coupled to one another via one or more first edges and each first edge in the one or more first edges has an associated weight value; generating, by the data processing system, a blinking graph model based on the graph, wherein the blinking graph model comprises blink rate values associated with second edges of the blinking graph model calculated based on weights of corresponding first edges in the input graph, wherein the blink rate value specifies a fraction of time a corresponding second edge is determined to be present in the blinking graph model; receiving, by the data processing system, a request for performance of a cognitive operation, wherein the request comprises an identification of a node of interest, calculating, by the data processing system, a relatedness metric for a target node in the blinking graph model relative to the node of interest based on the blink rate values of the second edges, wherein the relatedness metric indicates a degree of relatedness of the target node to the node of interest, wherein calculating the relatedness metric for the target node comprises calculating the relatedness metric for each path from the node of interest to a plurality of target nodes in the blinking graph model; and performing, by the data processing system, a cognitive operation based on the relatedness metric. 2. The method of claim 1 , wherein calculating the relatedness metric further comprises: identifying, by the data processing system, for the node of interest specified in the request for the cognitive operation, a first set of paths within the blinking graph model for which an exact calculation of a contribution to the relatedness metric of a target node is able to be calculated; and calculating, by the data processing system, for a combination of the node of interest and a second node associated with a path in the first set of paths, a first contribution to the relatedness metric based on the exact calculation associated with the path in the first set of paths.