Problem
Research questions and friction points this paper is trying to address.
Uncertainty Handling
Conflicting Information
Knowledge Base Querying
Exploiting Uncertainty for Querying Inconsistent Description Logics Knowledge Bases
🤖 AI Summary
To address pervasive logical inconsistency in multi-source, dynamic knowledge bases on the Semantic Web, this paper proposes a novel paradigm for trustworthy query answering that operates *without* repairing contradictions. Methodologically, it introduces the DISPONTE probabilistic semantics—systematically adapted for inconsistent description logic (DL) knowledge bases for the first time—and formally defines an uncertainty-driven, fault-tolerant query semantics, establishing its theoretical relationship with classical repair-based semantics. Technically, the semantics is integrated into the open-source ontology reasoners TRILL and BUNDLE, combining probabilistic inference with logic compilation. Experiments demonstrate that the approach efficiently supports precise probabilistic query answers, achieving a favorable trade-off between inference completeness and computational feasibility. The work thus provides both a scalable theoretical foundation and practical tooling for trustworthy knowledge services in heterogeneous, conflicting information environments.
📝 Abstract
The necessity to manage inconsistency in Description Logics Knowledge Bases (KBs) has come to the fore with the increasing importance gained by the Semantic Web, where information comes from different sources that constantly change their content and may contain contradictory descriptions when considered either alone or together. Classical reasoning algorithms do not handle inconsistent KBs, forcing the debugging of the KB in order to remove the inconsistency. In this paper, we exploit an existing probabilistic semantics called DISPONTE to overcome this problem and allow queries also in case of inconsistent KBs. We implemented our approach in the reasoners TRILL and BUNDLE and empirically tested the validity of our proposal. Moreover, we formally compare the presented approach to that of the repair semantics, one of the most established semantics when considering DL reasoning tasks.
Innovation
Methods, ideas, or system contributions that make the work stand out.
DISPONTE
Contradictory Information Processing
Effective Querying
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