A framework for context-sensitive metadata description

Khriyenko, Oleksiy; Terziyan, Vagan

doi:10.1504/ijmso.2006.011011

Cited by 15 publications

(11 citation statements)

References 6 publications

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“…Approaches [3,4,5,6,7,8,9,10,11,12,13,14] in the first category are all within the triple-based framework of standards from W3C, without modifying the semantics or introducing other additions. Some other researchers consider the limitation of triples as the main reason.…”

Section: Related Workmentioning

confidence: 99%

Towards applying dimensions to ontology

Jiang

Wan

Wang

et al. 2012

2012 International Conference on Information Management, Innovation Management and Industrial Engineering

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This paper will address the context-sensitive knowledge representation problem of ontology. The author regards the notion of context as a set of dimensions. The approach of applying dimensions to ontology is presented as a framework named Dimensional Ontology (DO). After analyzing different approaches for ontology contextualization, the author explores deeply the concepts and semantics of dimensions. Conforming to some standards, DO is designed and implemented as an integrated and extendable framework with multiple practical supporting components, which is one of the greatest advantages compared with other solutions.

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Section: Related Workmentioning

confidence: 99%

Towards applying dimensions to ontology

Jiang

Wan

Wang

et al. 2012

2012 International Conference on Information Management, Innovation Management and Industrial Engineering

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“…Its widespread popularity, user acceptance and abundance in the number of tools available for support justify our choice. This straight away rules out the options like quad-like models for representation of contextual RDF [19,9,16].…”

Section: Design and Implementationmentioning

confidence: 99%

Context shifting for effective search over large knowledge bases

Joseph

Serafini

Tamilin

2009

Proceedings of the 1st Workshop on Context, Information and Ontologies

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The problem of searching large knowledge bases is becoming an important facet of the current web of steadily proliferating semantic content. By pushing the notion of a context for partitioning large knowledge bases, performance of search is improved by narrowing the search space to a context of interest. On the other hand, by restricting the search only to a particular context, some answer can be missed, downgrading the search accuracy. In order to mitigate this drawback, we propose to extend the standard query algorithms with the operation of context shifting, i.e., the operation that allows switching to a close context, if the current context does not contain satisfactory information to answer a query. The paper provides a conceptual description of shifting in contextualized knowledge bases (CKB); and a prototypical implementation of a CKB that supports context shifting. For the conceptual description we adopt and extend the contextas-a-box paradigm introduced in [15]. In such a framework, a context is identified by a set of dimensions, whose values are taken from value-sets structured in hierarchies. Context shifting allows to switch from one context to another by changing the value of one or more dimensions along the corresponding hierarchies. For the prototypical implementation of a CKB we adopt and extend Sesame RDF store in order to support context shifting.

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“…This lead to the introduction of a growing number of logic based proposals, e.g. [5,6,9,10,11,12]. In this line of research, in our previous works we introduced the Contextualized Knowledge Repository (CKR) framework [9,4,1,3].…”

Section: Introductionmentioning

confidence: 99%

Knowledge Propagation in Contextualized Knowledge Repositories: An Experimental Evaluation

Bozzato

Serafini

2015

Lecture Notes in Computer Science

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Abstract. As the interest in the representation of context dependent knowledge in the Semantic Web has been recognized, a number of logic based solutions have been proposed in this regard. In our recent works, in response to this need, we presented the description logic-based Contextualized Knowledge Repository (CKR) framework. CKR is not only a theoretical framework, but it has been effectively implemented over state-of-the-art tools for the management of Semantic Web data: inference inside and across contexts has been realized in the form of forward SPARQL-based rules over different RDF named graphs. In this paper we present the first evaluation results for such CKR implementation. In particular, in first experiment we study its scalability with respect to different reasoning regimes. In a second experiment we analyze the effects of knowledge propagation on the computation of inferences.

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A framework for context-sensitive metadata description

Cited by 15 publications

References 6 publications

Towards applying dimensions to ontology

Towards applying dimensions to ontology

Context shifting for effective search over large knowledge bases

Knowledge Propagation in Contextualized Knowledge Repositories: An Experimental Evaluation

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