Recently, great efforts have been dedicated to researches on the management of large-scale graph-based data, where node disjoint subgraph homeomorphism relation between graphs has been shown to be more suitable than (sub)graph isomorphism in many cases, especially in those cases where node skipping and node mismatching are desired. However, no efficient algorithm for node disjoint subgraph homeomorphism determination (ndSHD) has been available. In this paper, we propose two computationally efficient ndSHD algorithms based on state spaces searching with backtracking, which employ many heuristics to prune the search spaces. Experimental results on synthetic data sets show that the proposed algorithms are efficient, require relatively little time in most of cases, can scale to large or dense graphs, and can accommodate to more complex fuzzy matching cases.
展开▼
