Simple fast algorithms for the editing distance between trees and related problems
SIAM Journal on Computing
The String-to-String Correction Problem
Journal of the ACM (JACM)
The Tree-to-Tree Correction Problem
Journal of the ACM (JACM)
Measuring Similarity between Ontologies
EKAW '02 Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web
Generic Schema Matching with Cupid
Proceedings of the 27th International Conference on Very Large Data Bases
A New Editing based Distance between Unordered Labeled Trees
CPM '93 Proceedings of the 4th Annual Symposium on Combinatorial Pattern Matching
Computing the Edit-Distance between Unrooted Ordered Trees
ESA '98 Proceedings of the 6th Annual European Symposium on Algorithms
Similarity Flooding: A Versatile Graph Matching Algorithm and Its Application to Schema Matching
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
The Knowledge Engineering Review
An Ontology Mapping Method Based on Tree Structure
SKG '06 Proceedings of the Second International Conference on Semantics, Knowledge, and Grid
COMA: a system for flexible combination of schema matching approaches
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Semantic Web Programming
An optimal decomposition algorithm for tree edit distance
ACM Transactions on Algorithms (TALG)
Similarity measure models and algorithms for hierarchical cases
Expert Systems with Applications: An International Journal
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A mapping-based tree similarity algorithm is proposed for matching concept trees in ontology alignment to integrate various information sources in the Semantic Web. Concepts regarding classes and properties are the most critical ontological elements and metadata. First, the similarity between the individual concepts of each type is defined. These concept systems, which are considered as the foundation of ontology, are described as tree modes for overall comparison. Based on the minimal cost of edit operations, previous tree similarity measuring approaches are extremely complicated because three or four edit operations are involved. Moreover, such approaches ignore the similarity among single nodes. In the proposed algorithm, node similarity, instead of changing operation, is adopted and the inserting and deleting operation is omitted. The proposed algorithm is more concise and effective because it satisfies the maximum mapping theorem without damaging tree isomorphism. The algorithm is resolved and realized by a dynamic programming scheme. Then, the algorithm is independently used to compare class and property trees, and their mapping concept sets are regarded as the main part of the ontology alignment. Demonstration examples are used to prove the effectiveness and feasibility of the algorithm in ontology alignment.