摘要:本体调试是人工智能中非标准推理任务之一，对于本体工程具有很重要的意义.结合互补概念与基于术语集的搜索图提出极小不可满足子术语集求解的优化方法.首先，通过判断扩展的术语集是否包含互补概念，确定该子术语集是否需要进行概念可满足性检测，可以有效减少推理机的调用次数.接着，根据术语集扩展过程构造一个术语集搜索图，分别采用宽度优先搜索和深度优先搜索策略快速查找不可满足子术语集.该优化方法一方面减少了待测子术语集的规模，另一方面提高了查找不可满足子术语集对应的节点的查找效率.最后，实现了所给出的各类优化算法并与现有的黑盒优化算法进行了比较.实验结果表明，该方法从推理机调用次数和待测术语集规模方面均优于现有的MUPS求解方法，能够有效提高求解术语集MUPS的效率.



Abstract:Ontology debugging is one of the non-standard reasoning tasks in artificial intelligence, and is important for ontology engineering. In this work, the complementary concepts and search graph are combined to optimize the calculation of minimal unsatisfiability preserving sub-TBox (MUPS) for the unsatisfiable concepts. Firstly, the necessity of checking the satisfaction of the concept for the expanded terminology is determined by whether it contains the complementary concepts to reduce the number of calling reasoners to some extent. Then, a search graph is constructed according to the terminology expanding process to quick search the node which is corresponding to the unsatisfiable sub-terminologies by breadth-first-search and depth-first-search strategies. This optimization reduces the number of axioms in terminologies to be checked, and it also improves the searching efficiency of the nodes corresponding to the unsatisfiable sub-terminologies. Finally, the optimized algorithms are realized and compared with existing black box algorithm. The experimental results show that the proposed method is superior to existing MUPS calculation in the calling number of reasoners and the number of axioms in the terminologies, which may effectively improve the efficiency of MUPS calculation.



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