scholarly journals Comparative Analysis of Merge Trees using Local Tree Edit Distance

2021 ◽  
pp. 1-1
Author(s):  
Raghavendra Sridharamurthy ◽  
Vijay Natarajan
Keyword(s):  
Comparative Analysis ◽  
Edit Distance ◽  
Tree Edit Distance

scholarly journals Tree Edit Distance Cannot be Computed in Strongly Subcubic Time (Unless APSP Can)

2020 ◽  
Vol 16 (4) ◽  
pp. 1-22
Author(s):  
Karl Bringmann ◽  
Paweł Gawrychowski ◽  
Shay Mozes ◽  
Oren Weimann
Keyword(s):  
Edit Distance ◽  
Tree Edit Distance

scholarly journals An optimal decomposition algorithm for tree edit distance

2009 ◽  
Vol 6 (1) ◽  
pp. 1-19 ◽  
Author(s):  
Erik D. Demaine ◽  
Shay Mozes ◽  
Benjamin Rossman ◽  
Oren Weimann
Keyword(s):  
Edit Distance ◽  
Decomposition Algorithm ◽  
Tree Edit Distance

scholarly journals Natural Language Inference for Arabic Using Extended Tree Edit Distance with Subtrees

2013 ◽  
Vol 48 ◽  
pp. 1-22 ◽  
Author(s):  
M. Alabbas ◽  
A. Ramsay
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Edit Distance ◽  
Arabic Text ◽  
Tree Edit Distance ◽  
Single Node ◽  
Preliminary Results ◽  
Standard Algorithm ◽  
Standard Tree

Many natural language processing (NLP) applications require the computation of similarities between pairs of syntactic or semantic trees. Many researchers have used tree edit distance for this task, but this technique suffers from the drawback that it deals with single node operations only. We have extended the standard tree edit distance algorithm to deal with subtree transformation operations as well as single nodes. The extended algorithm with subtree operations, TED+ST, is more effective and flexible than the standard algorithm, especially for applications that pay attention to relations among nodes (e.g. in linguistic trees, deleting a modifier subtree should be cheaper than the sum of deleting its components individually). We describe the use of TED+ST for checking entailment between two Arabic text snippets. The preliminary results of using TED+ST were encouraging when compared with two string-based approaches and with the standard algorithm.

XML SCHEMA MATCHING

2007 ◽  
Vol 17 (05) ◽  
pp. 575-597 ◽  
Author(s):  
JIANGUO LU ◽  
JU WANG ◽  
SHENGRUI WANG
Keyword(s):  
Data Integration ◽  
Software Reuse ◽  
Edit Distance ◽  
Xml Schema ◽  
Schema Matching ◽  
Schema Evolution ◽  
Tree Edit Distance ◽  
Matching Problem ◽  
Matching Algorithm ◽  
Unordered Trees

XML Schema matching problem can be formulated as follows: given two XML Schemas, find the best mapping between the elements and attributes of the schemas, and the overall similarity between them. XML Schema matching is an important problem in data integration, schema evolution, and software reuse. This paper describes a matching system that can find accurate matches and scales to large XML Schemas with hundreds of nodes. In our system, XML Schemas are modeled as labeled and unordered trees, and the schema matching problem is turned into a tree matching problem. We proposed Approximate Common Structures in trees, and developed a tree matching algorithm based on this concept. Compared with the traditional tree edit-distance algorithm and other schema matching systems, our algorithm is faster and more suitable for large XML Schema matching.

The Tree-Edit-Distance, a Measure for Quantifying Neuronal Morphology

2009 ◽  
Vol 7 (3) ◽  
pp. 179-190 ◽  
Author(s):  
Holger Heumann ◽  
Gabriel Wittum
Keyword(s):  
Edit Distance ◽  
Neuronal Morphology ◽  
Tree Edit Distance
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