OKBC: a programmatic foundation for knowledge base interoperability
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Conceptual-model-based data extraction from multiple-record Web pages
Data & Knowledge Engineering
Data & Knowledge Engineering
Modern Information Retrieval
Database Schema Matching Using Machine Learning with Feature Selection
CAiSE '02 Proceedings of the 14th International Conference on Advanced Information Systems Engineering
Answering queries using views: A survey
The VLDB Journal — The International Journal on Very Large Data Bases
A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Representing and reasoning about mappings between domain models
Eighteenth national conference on Artificial intelligence
Learning to match ontologies on the Semantic Web
The VLDB Journal — The International Journal on Very Large Data Bases
Ontology mapping: the state of the art
The Knowledge Engineering Review
iMAP: discovering complex semantic matches between database schemas
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
A composite approach to automating direct and indirect schema mappings
Information Systems
COMA: a system for flexible combination of schema matching approaches
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
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Ontologies on the Semantic Web are by nature decentralized. From the body of ontology mapping approaches, we can draw a conclusion that an effective approach to automate ontology mapping requires both data and metadata in application domains. Most existing approaches usually represent data and metadata by ad-hoc data structures, which lack formalisms to capture the underlying semantics. Furthermore, to approach semantic interoperability, there is a need to represent mappings between ontologies with well-defined semantics that guarantee accurate exchange of information. To address these problems, we propose that domain ontologies attached with extraction procedures are capable of representing knowledge required to find direct and indirect matches between ontologies. And mapping ontologies attached with query procedures not only support equivalent inferences and computations on equivalent concepts and relations but also improve query performance by applying query procedures to derive target-specific views. We conclude that a combination of declarative and procedural representation based on ontologies favors the analysis and implementation for ontology mapping that promises accurate and efficient semantic interoperability.