PossDL — A Possibilistic DL Reasoner for Uncertainty Reasoning and Inconsistency Handling

Qi, Guilin; Ji, Qiu; Pan, Jeff Z.; Du, Jianfeng

doi:10.1007/978-3-642-13489-0_35

Cited by 7 publications

(5 citation statements)

References 11 publications

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“…In this article, we justify such proposal and we develop a theory of OWL axiom testing against RDF facts based on possibility theory, whose output is a degree of possibility and necessity of an axiom, given the available evidence. Our proposal is coherent with a recently proposed possibilistic extension of description logics [17,18].…”

Section: Related Worksupporting

confidence: 72%

Possibilistic testing of OWL axioms against RDF data

Tettamanzi

Faron-Zucker

Gandon

2017

International Journal of Approximate Reasoning

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International audienceWe develop the theory of a possibilistic framework for OWL 2 axiom testing against RDF datasets, as an alternative to statistics-based heuristics. The intuition behind it is to evaluate the credibility of OWL 2 axioms based on the evidence available in the form of a set of facts contained in a chosen RDF dataset. To achieve it, we first define the notions of development, content, support , confirmation and counterexample of an axiom. Then we use these notions to define the possibility and necessity of an axiom and its acceptance/rejection index combining both of them. Finally, we report a practical application of the proposed framework to test SubClassOf axioms against the DBpedia RDF dataset

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Section: Related Worksupporting

confidence: 72%

Possibilistic testing of OWL axioms against RDF data

Tettamanzi

Faron-Zucker

Gandon

2017

International Journal of Approximate Reasoning

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“…In order to model epistemic uncertainty, soft ontologies have been defined within the possibilistic framework [57,58], that deals with certainty and possibility degrees of truth. Possibilistic ontologies aim at modeling the epistemic uncertainty characterizing experts' subjective knowledge and evaluation of the certainty of this knowledge.…”

Section: Ontologies and Soft Ontologiesmentioning

confidence: 99%

“…Possibilistic ontologies aim at modeling the epistemic uncertainty characterizing experts' subjective knowledge and evaluation of the certainty of this knowledge. To this end, several possibilistic DL reasoners have been defined [57,58] which allows representation and reasoning on uncertain statements such as "It is possible that this trail is a climbing trail". To this end each concept, relationships and axiom is associated to a real value α in (0, 1] representing its certainty level.…”

Section: Ontologies and Soft Ontologiesmentioning

confidence: 99%

A Semantic Approach for Quality Assurance and Assessment of Volunteered Geographic Information

Bordogna¹

2021

Information

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The paper analyses the characteristics of Volunteer Geographic Information (VGI) and the need to assure and assess its quality for a possible use and re-use. Ontologies and soft ontologies are presented as means to support quality assurance and assessment of VGI by highlighting their limitations. A proposal of a possibilistic approach using fuzzy ontology is finally illustrated that allows to model both imprecision and vagueness of domain knowledge and epistemic uncertainty affecting observations. A case study example is illustrated.

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“…It has been shown that checking the consistency degree and several inference services can be done with classical DLs reasoning services through consistent sub-sets of the Possibilistic-DLs KB. An implementation of a reasoner called DL-Poss, has been provided in [13]. A deeper discussion on Possibilistic-DLs has been provided in [14].…”

Section: Introductionmentioning

confidence: 99%

Possibilistic DL-Lite

Benferhat

Bouraoui

2013

Lecture Notes in Computer Science

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Abstract. DL-Lite is one of the most important fragment of description logics that allows a flexible representation of knowledge with a low computational complexity of the reasoning process. This paper investigates an extension of DL-Lite to deal with uncertainty associated with objects, concepts or relations using a possibility theory framework. Possibility theory offers a natural framework for representing uncertain and incomplete information. It is particularly useful for handling inconsistent knowledge. We first provide foundations of possibilistic DL-Lite, denoted by π-DL-Lite, where we present its syntax and its semantics. We then study the reasoning tasks and show how to measure the inconsistency degree of a knowledge base using query evaluations. An important result of the paper is that the extension of the expressive power of DL-Lite is done without additional extra computational costs.

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PossDL — A Possibilistic DL Reasoner for Uncertainty Reasoning and Inconsistency Handling

Cited by 7 publications

References 11 publications

Possibilistic testing of OWL axioms against RDF data

Possibilistic testing of OWL axioms against RDF data

A Semantic Approach for Quality Assurance and Assessment of Volunteered Geographic Information

Possibilistic DL-Lite

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