Abstract
Modularity clustering is an essential tool to understand complicated graphs. However, existing methods are not applicable to massive graphs due to
two serious weaknesses. (1) It is difficult to fully
reproduce ground-truth clusters due to the resolution limit problem. (2) They are computationally
expensive because all nodes and edges must be
computed iteratively. This paper proposes gScarf,
which outputs fine-grained clusters within a short
running time. To overcome the aforementioned
weaknesses, gScarf dynamically prunes unnecessary nodes and edges, ensuring that it captures finegrained clusters. Experiments show that gScarf
outperforms existing methods in terms of running
time while finding clusters with high accuracy