Track
Business Intelligence and Knowledge Management
Abstract
Business intelligence applications are being increasingly used to facilitate managerial insight and maintain competitiveness.These applications rely on the availability of integrated data from multiple data sources, making database integration anincreasingly important task. A central step in the process of data integration is schema matching, the identification of similarelements in the two databases. While a number of approaches have been proposed, the majority of schema matchingtechniques are based on ad-hoc heuristics, instead of an established theoretical foundation. The absence of a theoreticalfoundation makes it difficult to explain and improve schema matching process. This research surveys current cognitivetheories of similarity and demonstrates their application to the problem of schema matching. Better integration techniqueswill benefit business intelligence applications and can thereby contribute to business value.
Recommended Citation
Lukyanenko, Roman and Evermann, Joerg, "A Survey of Cognitive Theories to Support Data Integration" (2011). AMCIS 2011 Proceedings - All Submissions. 30.
https://aisel.aisnet.org/amcis2011_submissions/30