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 inserted and proved in two already reported FAS miners by speeding up their mining processes in artificial graph collections.
In REF , the authors proposed strategies to speed up the existing approximate mining algorithms, by limiting the number of candidates and also the number of duplicate checks performed.
On Speeding up Frequent Approximate Subgraph Mining
CIARP
Computer Science