document: Frequent subgraph mining in outerplanar graphs In recent years there has been an increased interest in algorithms that can perform frequent pattern discovery in large databases of graph structured objects . While the frequent connected subgraph mining problem for tree datasets can be solved in incremental polynomial time , it becomes intractable for arbitrary graph databases . Existing approaches have therefore resorted to various heuristic strategies and restrictions of the search space , but have not identified a practically relevant tractable graph class beyond trees . In this paper , we define the class of so called tenuous outerplanar graphs , a strict generalization of trees , develop a frequent subgraph mining algorithm for tenuous outerplanar graphs that works in incremental polynomial time , and evaluate the algorithm empirically on the NCI molecular graph dataset .
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