Before revision: Graph clustering objective functions with tunable resolution parameters make it possible to detect different types of clustering structure in the same graph. These objectives also provide a unifying view of other non-parametric objectives, which often can be captured as special cases.
After revision: Motivated by applications in community detection and dense subgraph discovery, we consider new clustering objectives in hypergraphs and bipartite graphs. These objectives are parameterized by one or more resolution parameters in order to enable diverse knowledge discovery in complex data. For both hypergraph and bipartite objectives, which often can be captured as special cases.