CLASSIC: a structural data model for objects
SIGMOD '89 Proceedings of the 1989 ACM SIGMOD international conference on Management of data
Proceedings of the 10th international conference on World Wide Web
Reconciling schemas of disparate data sources: a machine-learning approach
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Machine Learning
Product Data Integration in B2B E-Commerce
IEEE Intelligent Systems
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IEEE Intelligent Systems
A Two-Layered Integration Approach for Product Information in B2B E-commerce
EC-Web 2001 Proceedings of the Second International Conference on Electronic Commerce and Web Technologies
Proceedings of the Fifteenth International Florida Artificial Intelligence Research Society Conference
A Model to Support E-Catalog Integration
Proceedings of the IFIP TC2/WG2.6 Ninth Working Conference on Database Semantics: Semantic Issues in E-Commerce Systems
A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
MAFRA - A MApping FRAmework for Distributed Ontologies
EKAW '02 Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web
Context representation of product data
ACM SIGecom Exchanges
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AI Magazine
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ICEC '06 Proceedings of the 8th international conference on Electronic commerce: The new e-commerce: innovations for conquering current barriers, obstacles and limitations to conducting successful business on the internet
International Journal of Metadata, Semantics and Ontologies
Reconciling concepts and relations in heterogeneous ontologies
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
MostoDE: A tool to exchange data amongst semantic-web ontologies
Journal of Systems and Software
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The Semantic Web would enable new ways of doing business on the Web that require development of advanced business document integration technologies performing intelligent document transformation. The documents use different vocabularies that consist of large hierarchies of terms. Accordingly, vocabulary mapping and transformation becomes an important task in the whole business document transformation process. It includes several subtasks: map discovery, map representation, and map execution that must be seamlessly integrated into the document integration process. In this paper we discuss the process of discovering the maps between two vocabularies assuming availability of two sets of documents, each using one of the vocabularies. We take the vocabularies of product classification codes as a playground and propose a reusable map discovery technique based on Bayesian text classification approach. We show how the discovered maps can be integrated into the document transformation process.