Simple fast algorithms for the editing distance between trees and related problems
SIAM Journal on Computing
Maximum Agreement Subtree in a Set of Evolutionary Trees: Metrics and Efficient Algorithms
SIAM Journal on Computing
A System for Approximate Tree Matching
IEEE Transactions on Knowledge and Data Engineering
Information Processing Letters
Computing the Edit-Distance between Unrooted Ordered Trees
ESA '98 Proceedings of the 6th Annual European Symposium on Algorithms
DHC: A Density-Based Hierarchical Clustering Method for Time Series Gene Expression Data
BIBE '03 Proceedings of the 3rd IEEE Symposium on BioInformatics and BioEngineering
Unordered Tree Mining with Applications to Phylogeny
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
A survey on tree edit distance and related problems
Theoretical Computer Science
An optimal decomposition algorithm for tree edit distance
ICALP'07 Proceedings of the 34th international conference on Automata, Languages and Programming
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Clustering and classification hierarchies are organizational structures of a set of objects. Multiple hierarchies may be derived over the same set of objects, which makes distance computation between hierarchies an important task. In this paper, we model the classification and clustering hierarchies as rooted, leaf-labeled, unordered trees. We propose a novel distance metric Split-Order distance to evaluate the organizational structure difference between two hierarchies over the same set of leaf objects. Split-Order distance reflects the order in which subsets of the tree leaves are differentiated from each other and can be used to explain the relationships between the leaf objects. We also propose an efficient algorithm for computing Split-Order distance between two trees in O (n 2 d 4) time, where n is the number of leaves, and d is the maximum number of children of any node. Our experiments on both real and synthetic data demonstrate the efficiency and effectiveness of our algorithm.