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Automata-based axiom pinpointing
- Special Issue: Selected Papers from IJCAR’08
, 2010
"... Abstract. Axiom pinpointing has been introduced in description logics (DL) to help the user understand the reasons why consequences hold by computing minimal subsets of the knowledge base that have the conse-quence in question (MinA). Most of the pinpointing algorithms described in the DL literature ..."
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Abstract. Axiom pinpointing has been introduced in description logics (DL) to help the user understand the reasons why consequences hold by computing minimal subsets of the knowledge base that have the conse-quence in question (MinA). Most of the pinpointing algorithms described in the DL literature are obtained as extensions of tableau-based reason-ing algorithms for computing consequences from DL knowledge bases. In this paper, we show that automata-based algorithms for reasoning in DLs can also be extended to pinpointing algorithms. The idea is that the tree automaton constructed by the automata-based approach can be trans-formed into a weighted tree automaton whose so-called behaviour yields a pinpointing formula, i.e., a monotone Boolean formula whose minimal valuations correspond to the MinAs. We also develop an approach for computing the behaviour of a given weighted tree automaton. 1
A generic approach for large-scale ontological reasoning in the presence of access restrictions to the ontology’s axioms
- In Proc. of ISWC’09, volume 5823 of LNCS
, 2009
"... Abstract. The framework developed in this paper can deal with sce-narios where selected sub-ontologies of a large ontology are oered as views to users, based on criteria like the user's access right, the trust level required by the application, or the level of detail requested by the user. Inst ..."
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Abstract. The framework developed in this paper can deal with sce-narios where selected sub-ontologies of a large ontology are oered as views to users, based on criteria like the user's access right, the trust level required by the application, or the level of detail requested by the user. Instead of materializing a large number of dierent sub-ontologies, we propose to keep just one ontology, but equip each axiom with a la-bel from an appropriate labeling lattice. The access right, required trust level, etc. is then also represented by a label (called user label) from this lattice, and the corresponding sub-ontology is determined by compar-ing this label with the axiom labels. For large-scale ontologies, certain consequence (like the concept hierarchy) are often precomputed. Instead of precomputing these consequences for every possible sub-ontology, our approach computes just one label for each consequence such that a com-parison of the user label with the consequence label determines whether the consequence follows from the corresponding sub-ontology or not. In this paper we determine under which restrictions on the user and axiom labels such consequence labels (called boundaries) always exist, describe dierent black-box approaches for computing boundaries, and present rst experimental results that compare the eciency of these approaches on large real-world ontologies. Black-box means that, rather than requiring modications of existing reasoning procedures, these ap-proaches can use such procedures directly as sub-procedures, which al-lows us to employ existing highly-optimized reasoners. 1
On the Complexity of Axiom Pinpointing in the EL Family of Description Logics
, 2010
"... We investigate the computational complexity of axiom pin-pointing, which is the task of finding minimal subsets of a Description Logic knowledge base that have a given con-sequence. We consider the problems of enumerating such subsets with and without order, and show hardness results that already ho ..."
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Cited by 12 (3 self)
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We investigate the computational complexity of axiom pin-pointing, which is the task of finding minimal subsets of a Description Logic knowledge base that have a given con-sequence. We consider the problems of enumerating such subsets with and without order, and show hardness results that already hold for the propositional Horn fragment, or for the Description Logic EL. We show complexity results for several other related decision and enumeration problems for these fragments that extend to more expressive logics. In par-ticular we show that hardness of these problems depends not only on expressivity of the fragment but also on the shape of the axioms used.
Complexity of Axiom Pinpointing in the DL-Lite Family
"... In real world applications where ontologies are employed, often the knowledge engineer not only wants to know whether her ontology has a certain (unwanted) consequence or not, but also wants to know why it has this consequence. Even for ontologies of moderate size, finding explanations for a given c ..."
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In real world applications where ontologies are employed, often the knowledge engineer not only wants to know whether her ontology has a certain (unwanted) consequence or not, but also wants to know why it has this consequence. Even for ontologies of moderate size, finding explanations for a given consequence is
A generic approach for correcting access restrictions to a consequence
- In Proc. of ESWC 2010, volume 6088 of LNCS
, 2010
"... Abstract. Recent research has shown that annotations are useful for representing access restrictions to the axioms of an ontology and their implicit consequences. Previous work focused on assigning a label, rep-resenting its access level, to each consequence from a given ontology. However, a securit ..."
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Abstract. Recent research has shown that annotations are useful for representing access restrictions to the axioms of an ontology and their implicit consequences. Previous work focused on assigning a label, rep-resenting its access level, to each consequence from a given ontology. However, a security administrator might not be satisfied with the access level obtained through these methods. In this case, one is interested in finding which axioms would need to get their access restrictions modified in order to get the desired label for the consequence. In this paper we look at this problem and present algorithms for solving it with a variety of optimizations. We also present first experimental results on large scale ontologies, which show that our methods perform well in practice. 1
A Survey on how Description Logic Ontologies Benefit from FCA
"... Although the notion of a concept as a collection of objects sharing certain properties, and the notion of a conceptual hierarchy are fundamental to both Formal Concept Analysis and Description Logics, the ways concepts are described and obtained differ significantly between these two research areas ..."
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Cited by 4 (0 self)
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Although the notion of a concept as a collection of objects sharing certain properties, and the notion of a conceptual hierarchy are fundamental to both Formal Concept Analysis and Description Logics, the ways concepts are described and obtained differ significantly between these two research areas. Despite these differences, there have been several attempts to bridge the gap between these two formalisms, and attempts to apply methods from one field in the other. The present work aims to give an overview on the research done in combining Description Logics and Formal Concept Analysis.
The complexity of conjunctive query abduction in DL-Lite
, 2011
"... Abstract. In order to meet usability requirements, most logic-based applications provide explanation facilities for reasoning services. This holds also for DLs, where research focused on the explanation of both TBox reasoning and, more recently, query answering. Besides explaining the presence of a ..."
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Cited by 3 (2 self)
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Abstract. In order to meet usability requirements, most logic-based applications provide explanation facilities for reasoning services. This holds also for DLs, where research focused on the explanation of both TBox reasoning and, more recently, query answering. Besides explaining the presence of a tuple in a query answer, it is important to explain also why a given tuple is missing. We address this latter problem for (conjunctive) query answering over DL-Lite ontologies, by adopting abductive reasoning, that is, we look for additions to the ABox that force a given tuple to be in the result. As reasoning tasks, we consider existence and recognition of an explanation, and relevance and necessity of a certain assertion for an explanation. We characterize the computational complexity of these problems for subset minimal and cardinality minimal solutions. 1
H.: Query-based access control for ontologies
- In: Web Reasoning and Rule Systems
, 2010
"... Abstract. Role-based access control is a standard mechanism in information systems. Based on the role a user has, certain information is kept from the user even if requested. For ontologies representing knowledge, deciding what can be told to a user without revealing secrets is more difficult as the ..."
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Abstract. Role-based access control is a standard mechanism in information systems. Based on the role a user has, certain information is kept from the user even if requested. For ontologies representing knowledge, deciding what can be told to a user without revealing secrets is more difficult as the user might be able to infer secret knowledge using logical reasoning. In this paper, we present two approaches to solving this problem: query rewriting vs. axiom filtering, and show that while both approaches prevent the unveiling of secret knowledge, axiom fil-tering is more complete in the sense that it does not suppress knowledge the user is allowed to see while this happens frequently in query rewriting. Axiom filtering requires that each axiom carries a label representing its access level. We present methods to find an optimal axiom labeling to enforce query-based access restric-tions and report experiments on real world data showing that a significant number of results are retained using the axiom filtering method. 1
Adding Context to Tableaux for DLs
"... Abstract. We consider the problem of reasoning with ontologies where every axiom is associated to a context, and contexts are related through a total order. These contexts could represent, for example, a degree of trust associated to the axiom, or a level of granularity for the knowledge provided. W ..."
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Abstract. We consider the problem of reasoning with ontologies where every axiom is associated to a context, and contexts are related through a total order. These contexts could represent, for example, a degree of trust associated to the axiom, or a level of granularity for the knowledge provided. We describe an extension of tableaux-based decision procedures into methods that compute the best-fitting context for the consequences of an ontology, and apply it to the tableaux algorithm for ALC. We also describe an execution strategy that preserves most of the standard optimizations used in modern DL reasoners. 1