Frequent sub-graph mining entails two significant overheads. The first is concerned with candidate set generation. The second with isomorphism checking. These are also issues with ...
: In the complete graph K2m+3 for m 2, we study some structures of simple non-isomorphic Hamiltonian sub-graphs of the form H ( 2m+3 , 6m+3) for m 2 . The various structures of t...
The growth of the web has directly influenced the increase in the availability of relational data. One of the key problems in mining such data is computing the similarity between o...
Pradeep Muthukrishnan, Dragomir R. Radev, Qiaozhu ...
Existing frequent subgraph mining algorithms can operate efficiently on graphs that are sparse, have vertices with low and bounded degrees, and contain welllabeled vertices and edg...
Pattern mining methods for graph data have largely been restricted to ground features, such as frequent or correlated subgraphs. Kazius et al. have demonstrated the use of elaborat...
Andreas Maunz, Christoph Helma, Tobias Cramer, Ste...