Abstract
We introduce an abductive method for coherent composition of distributed data. Our approach is based on an abductive inference procedure that is applied on a meta-theory that relates different, possibly inconsistent, input databases. Repairs of the integrated data are computed, resultingin a consistent output database that satisfies the meta-theory. Our framework is based on the A-system, which is an abductive system that implements SLDNFA-resolution. The outcome is a robust application that, to the best of our knowledge, is more expressive (thus more general) than any other existing application for coherent data integration.
Cite
CITATION STYLE
Arieli, O., Van Nuffelen, B., Denecker, M., & Bruynooghe, M. (2001). Coherent composition of distributed knowledge-bases through abduction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2250, pp. 624–638). Springer Verlag. https://doi.org/10.1007/3-540-45653-8_43
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