Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Scaling Fine-grained Modularity Clustering for Massive Graphs   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 fine-grained clusters.
Experiments show that gScarf outperforms existing methods in terms of running
time while finding clusters with high accuracy.

35
The categories of this paper are: mtrl-th
18
The categories of this paper are: econ
29
The categories of this paper are: funct-an
26
The categories of this paper are: bayes-an
10
The categories of this paper are: q-bio
37
The categories of this paper are: supr-con
5
The categories of this paper are: gr-qc
12
The categories of this paper are: nucl-th
0
The categories of this paper are: hep-ph
23
The categories of this paper are: solv-int
36
The categories of this paper are: cmp-lg
27
The categories of this paper are: comp-gas
21
The categories of this paper are: adap-org
7
The categories of this paper are: hep-th
22
The categories of this paper are: chao-dyn
8
The categories of this paper are: hep-ex