Measuring General Relational Structure Using the Block Modularity Clustering Objective

The performance of all relational learning techniques has an implicit dependence on the underlying connectivity structure of the relations that are used as input. In this paper, we show how clustering can be used to develop an efficient optimization strategy can be used to effectively measure the structure of a graph in the absence of labeled instances.