Abstract
We study model-based diagnosis and propose a new approach of hybrid diagnosis combining black-box and white-box reasoning. We implemented and compared different diagnosis approaches including the standard hitting set algorithm and new approaches using answer set programming engines (DLV, Potassco) in the application of Euler/X toolkit, a logic-based toolkit for alignment of multiple biological taxonomies. Our benchmarks show that the new hybrid diagnosis approach runs about twice fast as the black-box diagnosis approach of the hitting set algorithm.
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Chen, M., Yu, S., Franz, N., Bowers, S., Ludäscher, B. (2014). A Hybrid Diagnosis Approach Combining Black-Box and White-Box Reasoning. In: Bikakis, A., Fodor, P., Roman, D. (eds) Rules on the Web. From Theory to Applications. RuleML 2014. Lecture Notes in Computer Science, vol 8620. Springer, Cham. https://doi.org/10.1007/978-3-319-09870-8_9
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DOI: https://doi.org/10.1007/978-3-319-09870-8_9
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