To overcome this feature sparseness problem, we propose a novel method based on graph decomposition to find candidate features for expanding feature vectors.
we first create a feature-relatedness graph, which is subsequently decomposed into core-periphery (CP) pairs and use the peripheries as the expansion candidates of the cores.