gSpan, an efficient algorithm for mining frequent subgraphs from a set of graphs (i.e., a graph dataset)

1. Download and install .NET Framework 4.0 (http://www.microsoft.com/en-us/download/details.aspx?id=17718).
2. Run the program.
3. Click Browse to select a graph dataset.
4. Specify the minimum support threshold (minSup).
5. Click "Mine data" to discover frequent subgraphs.
6. The result includes # of frequent subgraphs and runtime (in seconds).

If you use our source code, please cite the orginal gSpan paper and our paper as follows:

1. Xifeng Yan, Jiawei Han (2002). gspan: Graph-based substructure pattern mining. IEEE ICDM 2003, 721-724.
2. Bay Vo, Dang Nguyen, Thanh-Long Nguyen (2015). A parallel algorithm for frequent subgraph mining. ICCSAMA 2015, Metz, France. Springer AISC, 358, 163-173.

If you use the graph datasets, please cite our paper as follows:

1. Dang Nguyen, Wei Luo, Tu Dinh Nguyen, Svetha Venkatesh, Dinh Phung (2018). Learning Graph Representation via Frequent Subgraphs. SDM 2018, San Diego, USA. SIAM, 306-314.