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Merging data sources based on semantics, contexts and trust

ŠUBELJ, Lovro, JELENC, David, ZUPANČIČ, Eva, LAVBIČ, Dejan, TRČEK, Denis, KRISPER, Marjan, BAJEC, Marko. Merging data sources based on semantics, contexts and trust. IPSI BGD Trans. Internet Res.. [Print ed.], 2011, vol. 7, no. 1, str. 18-30, ilustr.


Matching and merging of data from heterogeneous sources is a common need in various scenarios. Despite numerous algorithms proposed in the recent literature, there is a lack of general and complete solutions combining different dimensions arising during the matching and merging execution.We propose a general framework, and accompanying algorithms, that allow joint control over various dimensions of matching and merging. To achieve superior performance, standard (relational) data representation is enriched with semantics and thus elevated towards the real world situation. Data sources are merged using collective entity resolution and redundancy elimination algorithms that are managed through the use of different contexts – user, data and also trust contexts. Introduction of trust allows for an adequate trust management and efficient security assurance which is, besides a general solution for matching and merging, the main novelty of the proposition.