Outerplanar graphs form a practically relevant class of graphs which appear efficiently computable bottom-up refinement operator for tenuous outerplanar graphs defined by combining techniques from first-order learning, algebraic graph theory, and combinatorial pattern matching. Since the coverage test for outerplanar graphs is decidable in polynomial time, our results can be used to develop practical algorithms for bottom-up induction of tenuous outerplanar graph patterns.
