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39
Completing description logic knowledge bases using formal concept analysis
- In Proc. of IJCAI 2007
, 2007
"... We propose an approach for extending both the terminological and the assertional part of a Description Logic knowledge base by using information provided by the knowledge base and by a domain expert. The use of techniques from Formal Concept Analysis ensures that, on the one hand, the interaction wi ..."
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Cited by 82 (7 self)
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We propose an approach for extending both the terminological and the assertional part of a Description Logic knowledge base by using information provided by the knowledge base and by a domain expert. The use of techniques from Formal Concept Analysis ensures that, on the one hand, the interaction with the expert is kept to a minimum, and, on the other hand, we can show that the extended knowledge base is complete in a certain, well-defined sense. 1
Ontology Learning
- HANDBOOK ON ONTOLOGIES
"... ... we show in this paper some exemplary techniques in the ontology learning cycle that we have implemented in our ontology learning environment, KAON Text-To-Onto. ..."
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Cited by 70 (3 self)
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... we show in this paper some exemplary techniques in the ontology learning cycle that we have implemented in our ontology learning environment, KAON Text-To-Onto.
DEBUGGING AND REPAIR OF OWL ONTOLOGIES
, 2006
"... With the advent of Semantic Web languages such as OWL (Web Ontology Language), the expressive Description Logic SHOIN is exposed to a wider audience of ontology users and developers. As an increasingly large number of OWL ontologies become available on the Semantic Web and the descriptions in the on ..."
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Cited by 57 (0 self)
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With the advent of Semantic Web languages such as OWL (Web Ontology Language), the expressive Description Logic SHOIN is exposed to a wider audience of ontology users and developers. As an increasingly large number of OWL ontologies become available on the Semantic Web and the descriptions in the ontologies become more complicated, finding the cause of errors becomes an extremely hard task even for experts. The problem is worse for newcomers to OWL who have little or no experience with DL-based knowledge representation. Existing ontology development environments, in conjunction with a reasoner, provide some limited debugging support, however this is restricted to merely reporting errors in the ontology, whereas bug diagnosis and resolution is usually left to the user. In this thesis, I present a complete end-to-end framework for explaining, pinpointing and repairing semantic defects in OWL-DL ontologies (or in other words, a SHOIN knowledge base). Semantic defects are logical contradictions that manifest as either inconsistent ontologies or unsatisfiable concepts. Where possible, I show extensions to handle related defects such as unsatisfiable roles, unintended entailments and nonentailments,
Axiom pinpointing in general tableaux
, 2010
"... Axiom pinpointing has been introduced in description logics (DLs) to help the user to understand the reasons why consequences hold and to remove unwanted consequences by computing minimal (maximal) subsets of the knowledge base that have (do not have) the consequence in question. Most of the pinpoin ..."
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Cited by 40 (9 self)
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Axiom pinpointing has been introduced in description logics (DLs) to help the user to understand the reasons why consequences hold and to remove unwanted consequences by computing minimal (maximal) subsets of the knowledge base that have (do not have) the consequence in question. Most of the pinpointing algorithms described in the DL literature are obtained as extensions of the standard tableau-based reasoning algorithms for computing consequences from DL knowledge bases. Although these extensions are based on similar ideas, they are all introduced for a particular tableau-based algorithm for a particular DL. The purpose of this paper is to develop a general approach for extending a tableau-based algorithm to a pinpointing algorithm. This approach is based on a general definition of “tableau algorithms,” which captures many of the known tableau-based algorithms employed in DLs, but also other kinds of reasoning procedures.
The role of domain ontologies in database design: An ontology management and conceptual modeling environment
- ACM Transactions on Database Systems (TODS
, 2006
"... Database design is difficult because it involves a database designer understanding an application and translating the design requirements into a conceptual model. However, the designer may have little or no knowledge about the application or task for which the database is being designed. This resear ..."
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Cited by 20 (0 self)
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Database design is difficult because it involves a database designer understanding an application and translating the design requirements into a conceptual model. However, the designer may have little or no knowledge about the application or task for which the database is being designed. This research presents a methodology for supporting database design creation and evaluation that makes use of domain-specific knowledge about an application stored in the form of domain ontologies. The methodology is implemented in a prototype system, the Ontology Management and Database Design Environment. Initial testing of the prototype illustrates that the incorporation and use of ontologies is effective in creating entity-relationship models.
Multimedia Interpretation for Dynamic Ontology Evolution
- JOURNAL OF LOGIC AND COMPUTATION, SPECIAL ISSUE ON ONTOLOGY DYNAMICS
, 2008
"... The recent success of distributed and dynamic infrastructures for knowledge sharing has raised the need for semiautomatic/automatic ontology evolution strategies. Ontology evolution is generally defined as the timely adaptation of an ontology to changing requirements and the consistent propagation o ..."
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Cited by 16 (10 self)
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The recent success of distributed and dynamic infrastructures for knowledge sharing has raised the need for semiautomatic/automatic ontology evolution strategies. Ontology evolution is generally defined as the timely adaptation of an ontology to changing requirements and the consistent propagation of changes to dependent artifacts. In this article, we present an ontology evolution approach in the context of multimedia interpretation. Ontology evolution in this context relies on the results obtained through reasoning for the interpretation of multimedia resources, through population of the ontology with new individuals, or through enrichment of the ontology with new concepts and new semantic relations. The article analyses the results of interpretation, population and enrichment obtained in evaluation experiments in terms of measures such as precision and recall. The evaluation reveals encouraging results.
Ontology dynamics with multimedia information: The boemie evolution methodology
- In International Workshop on Ontology Dynamics (IWOD-07
, 2007
"... Abstract. In this paper, we present the ontology evolution methodology developed in the context of the BOEMIE 4 project. Ontology evolution in BOEMIE relies on the results obtained through reasoning for the interpretation of multimedia resources in order to evolve (enhance) the ontology, through pop ..."
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Cited by 13 (3 self)
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Abstract. In this paper, we present the ontology evolution methodology developed in the context of the BOEMIE 4 project. Ontology evolution in BOEMIE relies on the results obtained through reasoning for the interpretation of multimedia resources in order to evolve (enhance) the ontology, through population of the ontology with new instances, or through enrichment of the ontology with new concepts and new semantic relations. 1
B.: Usability issues in description logic knowledge base completion
- In: ICFCA-2009
, 2009
"... Abstract. In a previous paper, we have introduced an approach for ex-tending both the terminological and the assertional part of a Description Logic knowledge base by using information provided by the assertional part and by a domain expert. This approach, called knowledge base com-pletion, was base ..."
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Cited by 7 (2 self)
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Abstract. In a previous paper, we have introduced an approach for ex-tending both the terminological and the assertional part of a Description Logic knowledge base by using information provided by the assertional part and by a domain expert. This approach, called knowledge base com-pletion, was based on an extension of attribute exploration to the case of partial contexts. The present paper recalls this approach, and then addresses usability issues that came up during first experiments with a preliminary implementation of the completion algorithm. It turns out that these issues can be addressed by extending the exploration algorithm for partial contexts such that it can deal with implicational background knowledge. 1
Ontology management for large-scale enterprise systems
- Electronic Commerce Research and Applications
"... been issued as a Research Report for early dissemination of its contents. In view of the transfer of copyright to the outside publisher, its distribution outside of IBM prior to publication should be limited to peer communications and specific requests. After outside publication, requests should be ..."
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Cited by 7 (1 self)
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been issued as a Research Report for early dissemination of its contents. In view of the transfer of copyright to the outside publisher, its distribution outside of IBM prior to publication should be limited to peer communications and specific requests. After outside publication, requests should be filled only by reprints or legally obtained copies of the article (e.g., payment of royalties). Copies may be requested from IBM T. J. Watson Research Center, P.
2008).“Intelligent approaches to mining the primary research literature: techniques, systems, and examples
- in Computational Intelligence in Medical Informatics, eds
"... The overwhelming amount of information available to the biomedical researcher makes the use of intelligent computational tools a necessity. These tools would help the researcher locate information appropriate to his or her goal, identify/extract the precise fragments of information required for each ..."
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Cited by 6 (1 self)
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The overwhelming amount of information available to the biomedical researcher makes the use of intelligent computational tools a necessity. These tools would help the researcher locate information appropriate to his or her goal, identify/extract the precise fragments of information required for each
