Journal ArticleDOI
The tree-to-tree editing problem
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TLDR
It is shown that a straightforward generalization of the Sankoff algorithm will provide a solution to the tree-to-tree editing problem and it follows that the algorithm must be optimal over a wide class of computation models.About:
This article is published in Information Processing Letters.The article was published on 1977-12-01. It has received 456 citations till now. The article focuses on the topics: Tree (data structure).read more
Citations
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Refactoring object-oriented frameworks
TL;DR: This thesis gives some conservative algorithms for determining whether a program satisfies constraints, and describes how to use this design information to refactor a program.
Journal ArticleDOI
The Tree-to-Tree Correction Problem
TL;DR: An algorithm is presented which solves the problem of determining the distance from T to T' as measured by the mlmmum cost sequence of edit operaUons needed to transform T into T'.
Proceedings ArticleDOI
Structural joins: a primitive for efficient XML query pattern matching
TL;DR: It is shown that, in some cases, tree-merge algorithms can have performance comparable to stack-tree algorithms, in many cases they are considerably worse, and this behavior is explained by analytical results that demonstrate that, on sorted inputs, the stack- tree algorithms have worst-case I/O and CPU complexities linear in the sum of the sizes of inputs and output, while the tree-MERge algorithms do not have the same guarantee.
Journal ArticleDOI
A survey on tree edit distance and related problems
TL;DR: This work surveys the problem of comparing labeled trees based on simple local operations of deleting, inserting, and relabeling nodes and presents one or more of the central algorithms for solving the problem.
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A Survey on Metric Learning for Feature Vectors and Structured Data
TL;DR: A systematic review of the metric learning literature is proposed, highlighting the pros and cons of each approach and presenting a wide range of methods that have recently emerged as powerful alternatives, including nonlinear metric learning, similarity learning and local metric learning.
References
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Journal ArticleDOI
The String-to-String Correction Problem
TL;DR: An algorithm is presented which solves the string-to-string correction problem in time proportional to the product of the lengths of the two strings.
Journal ArticleDOI
Matching Sequences under Deletion/Insertion Constraints
TL;DR: An economical algorithm is elaborated for finding subsequences satisfying deletion/insertion constraints and is useful in the study of genetic homology based on nucleotide or amino-acid sequences.
Journal ArticleDOI
Bounds on the Complexity of the Longest Common Subsequence Problem
TL;DR: It is shown that unless a bound on the total number of distinct symbols is assumed, every solution to the problem can consume an amount of time that is proportional to the product of the lengths of the two strings.
Journal ArticleDOI
Bounds for the String Editing Problem
C. K. Wong,Ashok K. Chandra +1 more
TL;DR: It is shown that if the operations on symbols of the strings are restricted to tests of equality, then O(nm) operations are necessary (and sufficient) to compute the distance between two strings.