An Algorithm for Finding the Largest Approximately Common Substructures of Two Trees
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reconciling schemas of disparate data sources: a machine-learning approach
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
A Graph-Oriented Model for Articulation of Ontology Interdependencies
EDBT '00 Proceedings of the 7th International Conference on Extending Database Technology: Advances in Database Technology
Identification of Syntactically Similar DTD Elements for Schema Matching
WAIM '01 Proceedings of the Second International Conference on Advances in Web-Age Information Management
Generic Schema Matching with Cupid
Proceedings of the 27th International Conference on Very Large Data Bases
A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
Similarity Flooding: A Versatile Graph Matching Algorithm and Its Application to Schema Matching
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
A Fast Tree Pattern Matching Algorithm for XML Query
WI '04 Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence
COMA: a system for flexible combination of schema matching approaches
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
An experiment on the matching and reuse of XML schemas
ICWE'05 Proceedings of the 5th international conference on Web Engineering
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This paper describes a matching algorithm that can find accurate matches and scales to large XML Schemas with hundreds of nodes. We model XML Schemas as labeled, unordered and rooted trees, and turn the schema matching problem into a tree matching problem. We develop a tree matching algorithm based on the concept of Approximate Common Structures. Compared with the tree edit-distance algorithm and other Schema matching systems, our algorithm is faster and more suitable for large XML Schema matching.