An Information-Theoretic Definition of Similarity
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
Measuring semantic similarity in the taxonomy of WordNet
ACSC '05 Proceedings of the Twenty-eighth Australasian conference on Computer Science - Volume 38
COMA: a system for flexible combination of schema matching approaches
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
XBenchMatch: a benchmark for XML schema matching tools
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Similarity of XML-Schema Elements
The Computer Journal
Using information content to evaluate semantic similarity in a taxonomy
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
A survey of schema-based matching approaches
Journal on Data Semantics IV
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A growing number of e-businesses have been using XML schemas in recent years. Schema mapping now plays a crucial role in integrating heterogeneous ebusiness applications. Since large-scale XML schema mapping using complex and hybrid similarity measures requires significant amount of processing time, a sophisticated similarity analysis algorithm is needed to handle its complexity and performance. In this paper, we focus on designing a service-oriented architecture (SoA) for schema mapping, based on a grid computing technology in order to enhance the effectiveness of the mapping algorithm. After comparing three different grid computing technologies (MPJ, Hadoop, and Globus), we explain why MPJ is the most suitable. We propose SoA XML schema mapping based on MPJ, and demonstrate its performance.