A Resolution Procedure for Description Logics with Nominal Schemas

Hitzler, Pascal

doi:10.1007/978-3-642-37996-3_1

Cited by 4 publications

(5 citation statements)

References 18 publications

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“…We have obtained this result by modifying an existing algorithm for EL ++ . While the algorithm modification itself is not overly sophisticated, it has taken considerable time (namely three years since the introduction of nominal schemas in [18]) and several previous unsuccessful efforts (such as [13,21]) to come up with this first approach. The main contribution of this paper is thus to show that a reasonable algorithmization of nominal-schema-extended description logics is feasible at all.…”

Section: Discussionmentioning

confidence: 99%

“…In fact, the unavailability of a folding-based normalization procedure is one of the main obstacles in adapting DL reasoning algorithms to nominal schemas, see [13,21]. Our approach presented below works without such a normalization as the underlying DL algorithm is based on Datalog.…”

Section: Definition 1 (Elrov N Restrictionsmentioning

confidence: 99%

“…However, despite this, first attempts to arrive at an efficient algorithmization of reasoning with nominal schemas have had limited success: [13] reported on a corresponding extension of tableaux algorithms, while [21] reported on a resolution-based algorithm for the tractable fragment-but neither of these algorithms looks promising enough in terms of scalability to even attempt an implementation.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Towards an Efficient Algorithm to Reason over Description Logics Extended with Nominal Schemas

Carral

Hitzler

2013

Web Reasoning and Rule Systems

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Abstract. Extending description logics with so-called nominal schemas has been shown to be a major step towards integrating description logics with rules paradigms. However, establishing efficient algorithms for reasoning with nominal schemas has so far been a challenge. In this paper, we present an algorithm to reason with the description logic fragment ELROVn, a fragment that extends EL ++ with nominal schemas. We also report on an implementation and experimental evaluation of the algorithm, which shows that our approach is indeed rather efficient.

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Section: Discussionmentioning

confidence: 99%

Section: Definition 1 (Elrov N Restrictionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Towards an Efficient Algorithm to Reason over Description Logics Extended with Nominal Schemas

Carral

Hitzler

2013

Web Reasoning and Rule Systems

Self Cite

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“…The complexities of different DL languages extended with nominal schemas are studied in [30]. However, despite this, first attempts to arrive at an efficient reasoning algorithm with nominal schemas have had limited success: [24] reported on a corresponding extension of tableaux algorithms, while [42] reported on a resolution-based algorithm for the tractable fragment-but neither of these algorithms looked promising enough in terms of scalability to even attempt an implementation. However, an adaptation of the reasoning optimization technique known as absorption has led to a significantly improved reasoning algorithm with nominal-schema-extended SROIQ [37,38]; that is, the logic underlying the OWL DL language.…”

Section: Summary Of Related Workmentioning

confidence: 99%

An efficient algorithm for reasoning over OWL EL ontologies with nominal schemas

Carral

Zalewski

Hitzler

2022

Journal of Logic and Computation

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Nominal schemas have been proposed as an extension to Description Logics (DL), the knowledge representation paradigm underlying the Web Ontology Language (OWL). They provide for a very tight integration of DL and rules. Nominal schemas can be understood as syntactic sugar on top of OWL. However, this naive perspective leads to inefficient reasoning procedures. In order to develop an efficient reasoning procedure for the language ${\mathcal {E}\mathcal {L}\mathcal {V}^{++}}$, which results from extending the OWL profile language OWL EL with nominal schemas, we propose a transformation from ${\mathcal {E}\mathcal {L}\mathcal {V}^{++}}$ ontologies into Datalog-like rule programs that can be used for satisfiability checking and assertion retrieval. The use of this transformation enables the use of powerful Datalog engines to solve reasoning tasks over ${\mathcal {E}\mathcal {L}\mathcal {V}^{++}}$ ontologies. We implement and then evaluate our approach on several real-world, data-intensive ontologies, and find that it can outperform state-of-the-art reasoners such as Konclude and ELK. As a lesser side result we also provide a self-contained description of a rule-based algorithm for ${\mathcal {E}\mathcal {L}^{++}}$, which does not require a normal form transformation.

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“…Nominal resolution and effective resolution The nominal resolution [11] nom R refers to the length between the neighbouring sampling points. As introduced before, various aliasing and noises exist in different areas of the dual grid.…”

Section: Adaptive Reciprocal Cellmentioning

confidence: 99%

Remote sensing image restoration: adaptive reciprocal cell recovery technique

Shu¹,

Sun²,

Li³

et al. 2018

ITC

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Improving the quality of remote sensing images is of great value for subsequent applications. In order to reduce the noise and blur of remote sensing images, the deblurring restoration technology is studied in this paper. Firstly, the acquisition of remote sensing image and the causes of image degradation are briefly analyzed. It was found that noise, blur and aliasing had great influence on image quality. Then, based on adaptive reciprocal cell, a method of titling mode restoration is proposed, which was achieved by generating adaptive reciprocal cell, extracting effective spectrum and deblurring. In order to verify the validity of the method, TV model, ARCTV model and ARCNLM model were used to restore a synthetic image and two scene images. The results showed that the Signal Noise Ratio (SNR) of the ARCNLM model was higher than that of other models, and its mean square error (MSE) was lower than that of other models. Moreover, ARCNLM model had better deblurring effect than other models, and it could not only effectively remove aliasing, but also could maintain the texture and details of the image. The experimental results suggested the effectiveness of ARCNLM model in image restoration and provided some basis for its practical application in image restoration.

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A Resolution Procedure for Description Logics with Nominal Schemas

Cited by 4 publications

References 18 publications

Towards an Efficient Algorithm to Reason over Description Logics Extended with Nominal Schemas

Towards an Efficient Algorithm to Reason over Description Logics Extended with Nominal Schemas

An efficient algorithm for reasoning over OWL EL ontologies with nominal schemas

Remote sensing image restoration: adaptive reciprocal cell recovery technique

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