A Knowledge-Based Framework for Data Integration
Mudan Cao, Ding Xiao, Yijun Liu, Yi Xiang Tong
Abstract
Mudan Cao, Ding Xiao, Yijun Liu, Yi Xiang Tong
Abstract
Aiming at integrating heterogeneous data sources into a logic unified data view, data integration has drawn considerable attention. This paper proposes a novel knowledge-based framework for data integration within which schema integration and content integration are two focal modules. A constructive semantic recommendation algorithm is put forward for schema integration, and a rule-based cleansing procedure is summarized for content integration. Experiments validate the effectiveness and efficiency of the proposed algorithms and thus verify the framework is feasible and pragmatic.
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Aiming at integrating heterogeneous data sources into a logic unified data view, data integration has drawn considerable attention. This paper proposes a novel knowledge-based framework for data integration within which schema integration and content integration are two focal modules. A constructive semantic recommendation algorithm is put forward for schema integration, and a rule-based cleansing procedure is summarized for content integration. Experiments validate the effectiveness and efficiency of the proposed algorithms and thus verify the framework is feasible and pragmatic.
Key concepts: Data integration, Computer science, Schema (genetic algorithms), Constructive, Information integration, Knowledge integration, Data mining, Information retrieval