2 research outputs found

    Faster Algorithms for the Maximum Common Subtree Isomorphism Problem

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    The maximum common subtree isomorphism problem asks for the largest possible isomorphism between subtrees of two given input trees. This problem is a natural restriction of the maximum common subgraph problem, which is NP{\sf NP}-hard in general graphs. Confining to trees renders polynomial time algorithms possible and is of fundamental importance for approaches on more general graph classes. Various variants of this problem in trees have been intensively studied. We consider the general case, where trees are neither rooted nor ordered and the isomorphism is maximum w.r.t. a weight function on the mapped vertices and edges. For trees of order nn and maximum degree Δ\Delta our algorithm achieves a running time of O(n2Δ)\mathcal{O}(n^2\Delta) by exploiting the structure of the matching instances arising as subproblems. Thus our algorithm outperforms the best previously known approaches. No faster algorithm is possible for trees of bounded degree and for trees of unbounded degree we show that a further reduction of the running time would directly improve the best known approach to the assignment problem. Combining a polynomial-delay algorithm for the enumeration of all maximum common subtree isomorphisms with central ideas of our new algorithm leads to an improvement of its running time from O(n6+Tn2)\mathcal{O}(n^6+Tn^2) to O(n3+TnΔ)\mathcal{O}(n^3+Tn\Delta), where nn is the order of the larger tree, TT is the number of different solutions, and Δ\Delta is the minimum of the maximum degrees of the input trees. Our theoretical results are supplemented by an experimental evaluation on synthetic and real-world instances

    Largest Weight Common Subtree Embeddings with Distance Penalties

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    The largest common embeddable subtree problem asks for the largest possible tree embeddable into two input trees and generalizes the classical maximum common subtree problem. Several variants of the problem in labeled and unlabeled rooted trees have been studied, e.g., for the comparison of evolutionary trees. We consider a generalization, where the sought embedding is maximal with regard to a weight function on pairs of labels. We support rooted and unrooted trees with vertex and edge labels as well as distance penalties for skipping vertices. This variant is important for many applications such as the comparison of chemical structures and evolutionary trees. Our algorithm computes the solution from a series of bipartite matching instances, which are solved efficiently by exploiting their structural relation and imbalance. Our analysis shows that our approach improves or matches the running time of the formally best algorithms for several problem variants. Specifically, we obtain a running time of O(|T| |T\u27|Delta) for two rooted or unrooted trees T and T\u27, where Delta=min{Delta(T),Delta(T\u27)} with Delta(X) the maximum degree of X. If the weights are integral and at most C, we obtain a running time of O(|T| |T\u27|sqrt Delta log (C min{|T|,|T\u27|})) for rooted trees
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