Mining for Unconnected Frequent Graphs with Direct Subgraph Isomorphism Tests

In the paper we propose the algorithm which discovers both connected and unconnected frequent graphs from the graphs set. Our approach is based on depth first search candidate generation and direct execution of subgraph isomorphism test over database. Several search space pruning techniques are also proposed. Due to lack of unconnected graph mining algorithms we compare our algorithm with two general techniques which make unconnected graph discovery possible by means of connected graph mining algorithms. We also perform undirected comparison of our algorithm with connected graph mining algorithms by comparing the number of discovered frequent subgraphs per second. Finally we derive a connected graph mining algorithm from our algorithm and show that it is competitive (though not winning) with popular connected graph mining algorithms.