gCore mode [graph_path graph_name] [options]
cs Run case study.
grk Generate random \mathbf{k} vectors.
grp Generate random \mathbf{p} vectors.
grkp Generate random (\mathbf{k},\mathbf{p}) vector pairs.
pgcs Compare the efficiency of CORE, dCC and GCS on pillar multi-layer graphs.
bp Build P-tree.
bkp Build KP-tree.
gcs Compare the efficiency of CORE, dCC(pillar mlg only), RCD(general mlg only), GCS and (K)P-tree-based search (under different P-tree compaction levels).
gcii Show statistics of GCI, including construction time, memory cost and number of nodes.
kv Compare the k-value of nodes in the (\mathbf{k},\mathbf{p})-core, the (\mathbf{k},\mathbf{ck})-rcd and the k-core.
pv Compare the p-value of nodes in the (\mathbf{k},\mathbf{p})-core, the (\mathbf{k},\mathbf{ck})-rcd and the k-core.
sm Compute the size distribution when varying \mathbf{k}[i] and \mathbf{p}[i] for each layer i.
smk Compute the size distribution when fixing \mathbf{k} and varying \mathbf{p}[i] for each layer i.
info Compute basic information of the loaded multi-layer graph.
-ntc Number of testcases.
-skf File of sampled coreness vectors (\mathbf{k}).
-spf File of sampled fraction vectors (\mathbf{p}).
-skpf File of sampled (\mathbf{k}, \mathbf{p}) vector pairs.
-k Coreness vector (\mathbf{k}).
-p Neighbor coverage fraction vector (\mathbf{p}).
-b/pb P-tree builder.
-s Incremental step of coreness vectors to construct P-trees.
-o Output path.
-ik Start/Initial coreness vector.
-ck Cross-layer degree threshold vector.
-pk Coreness threshold for the selected layer.
-ptf P-tree file.
-kptf KP-tree file.
-f2if Fraction to index map file.
-ps Incremental step of fraction vectors to compute size matrices.
-ek End coreness vector.
-d/dim Dimension.
-g Graph to perform case study, "dblp" and "twitter" are availiable.
naive Build P-tree without optimization.
ne Build compact P+-tree with subtree elimination.
se Build compact P+-DAG with subtree merge
nese Build compact P+-DAG with both subtree elimination and subtree merge.