Resolution-Based Reasoning for Ontologies.
Handbook on Ontologies(2009)
摘要
We overview the algorithms for reasoning with description logic (DL) ontologies based on resolution. These algorithms often
have worst-case optimal complexity, and, by relying on vast experience in building resolution theorem provers, they can be
implemented efficiently. Furthermore, we present a resolution-based algorithm that reduces a DL knowledge base into a disjunctive
datalog program, while preserving the set of entailed facts. This reduction enables the application of optimization techniques
from deductive databases, such as magic sets, to reasoning in DLs. This approach has proven itself in practice on ontologies
with relatively small and simple TBoxes, but large ABoxes.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络