On speeding up frequent approximate subgraph mining

Abstract

Frequent approximate subgraph (FAS) mining has become an interesting task with wide applications in several domains of science. Most of the previous studies have been focused on reducing the search space or the number of canonical form (CF) tests. CF-tests are commonly used for duplicate detection; however, these tests affect the efficiency of mining process because they have high computational complexity. In this paper, two prunes are proposed, which allow decreasing the label space, the number of candidates and the number of CF-tests. The proposed prunes are already used and validated in two reported FAS miners by speeding up their mining processes in artificial graph collections. © 2012 Springer-Verlag.