Abstract
Hybrid knowledge bases (HKB’s) [11] were developed to provide formal models for the mediation of data and knowledge bases [14,15]. They are based on Generalized Annotated Logic Programming (GAP)[7] and employ an inference mechanism, HKB-resolution, that is considerably simpler than those that have been proposed for GAP. The simplicity of HKB-resolution is explained in this paper by showing that it is a special case of ℧-resolution, which was introduced in [9]. A generalization of ℧-resolution to lattices that are not ordinary is also explored.
This research was supported in part by the National Science Foundation under grants CCR-9731893, CCR-9404338 and CCR-9504349.
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Lu, J.J., Murray, N.V., Rosenthal, E. (1999). A Foundation for Hybrid Knowledge Bases. In: Rangan, C.P., Raman, V., Ramanujam, R. (eds) Foundations of Software Technology and Theoretical Computer Science. FSTTCS 1999. Lecture Notes in Computer Science, vol 1738. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46691-6_12
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DOI: https://doi.org/10.1007/3-540-46691-6_12
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