RECUT: RE-Compressing partially Unordered Trees

2018 ◽  
Author(s):  
Stefan Bottcher ◽  
Rita Hartel
Keyword(s):  
Unordered Trees

scholarly journals Algorithmic height compression of unordered trees

2016 ◽  
Vol 389 ◽  
pp. 237-252
Author(s):  
Farah Ben-Naoum ◽  
Christophe Godin
Keyword(s):  
Unordered Trees

scholarly journals Logics for unordered trees with data constraints

2019 ◽  
Vol 104 ◽  
pp. 149-164 ◽  
Author(s):  
Adrien Boiret ◽  
Vincent Hugot ◽  
Joachim Niehren ◽  
Ralf Treinen
Keyword(s):  
Unordered Trees ◽  
Data Constraints

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.

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