Open AccessJournal Article
Explaining User Errors in Knowledge Base Completion.
TL;DR: The problem of explaining user errors in knowledge base completion is considered, and it is shown that for this setting, the problem of deciding the existence of an explanation within a specified cardinality bound is NP-complete, and theproblem of counting explanations that are minimal w.r.t. set inclusion is #P-complete.
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Abstract: Knowledge base completion is a method for extending both the terminological and assertional part of a Description Logic knowledge base by using information provided by a domain expert. It ensures that the extended knowledge base is complete w.r.t. a fixed interpretation in a certain, well-defined sense. Here we consider the problem of explaining user errors in knowledge base completion. We show that for this setting, the problem of deciding the existence of an explanation within a specified cardinality bound is NP-complete, and the problem of counting explanations that are minimal w.r.t. set inclusion is #P-complete. We also provide an algorithm that computes one minimal explanation by performing at most polynomially many subsumption tests.
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Citations
Finding Small Proofs for Description Logic Entailments: Theory and Practice (Extended Technical Report).
TL;DR: In this article, the authors introduce a general framework in which proofs are represented as labeled, directed hypergraphs, where each hyperedge corresponds to a single sound derivation step.
Research progress of large-scale knowledge graph completion technology
Shuo Wang,Shuo Wang,Zhijuan Du,Xiaofeng Meng +3 more
- 13 Apr 2020
TL;DR: The challenges that the technology will face and the development prospects of future work are presented, including RDF triples completion learning, which includes entity completion or relationship completion and is described in three development stages, such as statistical relational learning, probability learning based on random walks, and knowledge representation learning.
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