Principles of artificial intelligence
Principles of artificial intelligence
Graph minors. XIII: the disjoint paths problem
Journal of Combinatorial Theory Series B
An Algorithm for Subgraph Isomorphism
Journal of the ACM (JACM)
Computers and Intractability; A Guide to the Theory of NP-Completeness
Computers and Intractability; A Guide to the Theory of NP-Completeness
RECOMB '04 Proceedings of the eighth annual international conference on Resaerch in computational molecular biology
Discovering frequent topological structures from graph datasets
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Frequent approximate subgraphs as features for graph-based image classification
Knowledge-Based Systems
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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.