Mining graph data is an increasingly popular challenge, which has practical applications in many areas, including molecular substructure discovery, web link analysis, fraud detect...
The problem of discovering frequent subgraphs of graph data can be solved by constructing a candidate set of subgraphs first, and then, identifying within this candidate set those...
We describe an approach for interactive collision detection and proximity computations on massive models composed of millions of geometric primitives. We address issues related to...
Andy Wilson, Eric Larsen, Dinesh Manocha, Ming C. ...
In this paper, we present a tree-partition algorithm for parallel mining of frequent patterns. Our work is based on FP-Growth algorithm, which is constituted of tree-building stag...
Attributed graphs are increasingly more common in many application domains such as chemistry, biology and text processing. A central issue in graph mining is how to collect inform...