$\mathcal{F}$ lora-2: A Rule-Based Knowledge Representation and Inference Infrastructure for the Semantic Web

Yang, Guang; Kifer, Michael; Zhao, Chang

doi:10.1007/978-3-540-39964-3_43

Cited by 69 publications

(35 citation statements)

References 24 publications

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“…In [6], we reviewed and compared ERDF with the following older extensions of web ontology languages with rules [68,67,65,70,13,1,8,10,18,43,54,21,22,61,62]. Additionally, at the end of this Section, we provide a comparison of the #n-stable model semantics on general ERDF ontologies with other semantics of logic programs with rules of a richer (than normal programs) syntax.…”

Section: Related Workmentioning

confidence: 99%

Extended RDF: Computability and complexity issues

Analyti

Damásio

Antoniou

2015

Ann Math Artif Intell

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Abstract. ERDF stable model semantics is a recently proposed semantics for ERDF ontologies and a faithful extension of RDFS semantics on RDF graphs. In this paper, we elaborate on the computability and complexity issues of the ERDF stable model semantics. Based on the undecidability result of ERDF stable model semantics, decidability under this semantics cannot be achieved, unless ERDF ontologies of restricted syntax are considered. Therefore, we propose a slightly modified semantics for ERDF ontologies, called ERDF #n-stable model semantics. We show that entailment under this semantics is, in general, decidable and also extends RDFS entailment. Equivalence statements between the two semantics are provided. Additionally, we provide algorithms that compute the ERDF #n-stable models of syntax-restricted and general ERDF ontologies. Further, we provide complexity results for the ERDF #n-stable model semantics on syntax-restricted and general ERDF ontologies. Finally, we provide complexity results for the ERDF stable model semantics on syntax-restricted ERDF ontologies.

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Section: Related Workmentioning

confidence: 99%

Extended RDF: Computability and complexity issues

Analyti

Damásio

Antoniou

2015

Ann Math Artif Intell

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“…Our service discovery component uses f-Logic to describe capabilities, goals and to make queries using FLORA-2 reasoner [10] for matchmaking capabilities and goals. In goals, we model the precondition (the state of the information space before executing a web service) and the postcondition (the state of the information space that is desired).…”

Section: Discoverymentioning

confidence: 99%

How to Make It Faster and at Lower Cost? B2B Integration with Semantic Web Services

Losada

Keczek

Benjamins

et al. 2006

17th International Workshop on Database and Expert Systems Applications (DEXA'06)

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“…Rule prioritization is part of Courteous Logic Programming [Gro99], and is supported by the Sweet Rules system. 9 Object-oriented extensions inspired by F-logic [KLW95] and HiLog higher-order extensions [CKW93] are part of the FLORA-2 system [YKZ03]. In fact, SWSL-Rules -a language that incorporates all of these layers have also been recently proposed [BBB + 05].…”

Section: The Underpinnings Of the Rules Stackmentioning

confidence: 99%

“…Scoped inference is an important feature of several knowledge representation systems for the Web. In FLORA-2 [YKZ03], the entire knowledge base is split into modules and inference is always made with respect to a particular module. In TRIPLE [SD02], the same idea goes under the name of a context.…”

Section: Scoped Inferencementioning

confidence: 99%

A Realistic Architecture for the Semantic Web

Kifer

Bruijn

Boley³

et al. 2005

Lecture Notes in Computer Science

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Abstract. In this paper we argue that a realistic architecture for the Semantic Web must be based on multiple independent, but interoperable, stacks of languages. In particular, we argue that there is a very important class of rule-based languages, with over thirty years of history and experience, which cannot be layered on top of OWL and must be included in the Semantic Web architecture alongside with the stack of OWL-based languages. The class of languages we are after includes rules in the Logic Programming style, which support default negation. We briefly survey the logical foundations of these languages and then discuss an interoperability framework in which such languages can co-exist with OWL and its extensions.

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$\mathcal{F}$ lora-2: A Rule-Based Knowledge Representation and Inference Infrastructure for the Semantic Web

Cited by 69 publications

References 24 publications

Extended RDF: Computability and complexity issues

Extended RDF: Computability and complexity issues

How to Make It Faster and at Lower Cost? B2B Integration with Semantic Web Services

A Realistic Architecture for the Semantic Web

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