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A Hybrid Diagnosis Approach Combining Black-Box and White-Box Reasoning

  • Mingmin Chen
  • Shizhuo Yu
  • Nico Franz
  • Shawn Bowers
  • Bertram Ludäscher
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8620)

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.

Keywords

Hybrid Approach Boolean Expression Proof Tree Taxonomic Concept Diagnosis Approach 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Mingmin Chen
    • 1
  • Shizhuo Yu
    • 1
  • Nico Franz
    • 2
  • Shawn Bowers
    • 3
  • Bertram Ludäscher
    • 1
  1. 1.Dept. of Computer ScienceUniversity of CaliforniaDavisUSA
  2. 2.School of Life SciencesArizona State UniversityUSA
  3. 3.Dept. of Computer ScienceGonzaga UniversityUSA

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