International Business Machines Corporation
Partitioning knowledge graph

Abstract:

A method for partitioning a knowledge graph is provided. The method analyzes past searches and determines an access frequency of a plurality of edges. The method marks, as intermediate cluster cores, edges having the highest access frequencies, sorts the marked intermediate cluster cores according to their access frequencies, and selects a first cluster core having the highest access frequency. The method assigns first edges in a first radius around the first cluster core to build the first cluster. The method selects a second cluster core having the highest access frequency apart from edges of the first cluster, and assigns second edges in a second radius around second cluster core to build the second cluster. The method partitions the knowledge graph into a first sub-knowledge-graph comprising the first cluster and a second sub-knowledge-graph comprising the second cluster.