An overview of fuzzy Description Logics for the Semantic Web

Ma, Zongmin; Zhang, Fu; Wang, Hailong; Li, Yan

doi:10.1017/s0269888912000306

Cited by 12 publications

(12 citation statements)

References 133 publications

(356 reference statements)

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“…According to the fuzzy DLs introduced in Lukasiewicz and Straccia (2008), , and Ma et al (2013), in this section we will recall and introduce the existing fuzzy DLs and their relevant reasoning techniques. In fact, as we have known that the reasoning of fuzzy ontologies is based on the reasoning mechanisms of fuzzy DLs, as the logical underpinnings of the fuzzy ontology representation language OWL are mainly expressive fuzzy DLs such as f-SHIF(D) and f-SHOIN(D) as mentioned in Section 3.…”

Section: Reasoning Of Fuzzy Ontologiesmentioning

confidence: 99%

“…The more detailed introduction about the fuzzy DLs and the reasoning techniques of fuzzy DLs can be found in Lukasiewicz and Straccia (2008), , and Ma et al (2013). Before that, it is necessary for us to survey the existing fuzzy DLs first.…”

Section: Reasoning On Fuzzy Description Logics and Fuzzy Ontologiesmentioning

confidence: 99%

“…Also, how to represent and reason on fuzzy UML models with the fuzzy DL was presented by Ma et al . (2011b). Moreover, Zhang et al .…”

Section: Applications and Other Issues Of Fuzzy Ontologiesmentioning

confidence: 99%

“…In fact, as we have known that the reasoning of fuzzy ontologies is based on the reasoning mechanisms of fuzzy DLs, as the logical underpinnings of the fuzzy ontology representation language OWL are mainly expressive fuzzy DLs such as f-SHIF(D) and f-SHOIN(D) as mentioned in Section 3. According to the fuzzy DLs introduced in Lukasiewicz and Straccia (2008), , and Ma et al (2013), in this section we will recall and introduce the existing fuzzy DLs and their relevant reasoning techniques.…”

Section: Reasoning Of Fuzzy Ontologiesmentioning

confidence: 99%

“…Before that, it is necessary for us to survey the existing fuzzy DLs first. The more detailed introduction about the fuzzy DLs and the reasoning techniques of fuzzy DLs can be found in Lukasiewicz and Straccia (2008), , and Ma et al (2013).…”

Section: Reasoning On Fuzzy Description Logics and Fuzzy Ontologiesmentioning

confidence: 99%

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A survey on fuzzy ontologies for the Semantic Web

Zhang¹,

Cheng²,

Ma³

2016

The Knowledge Engineering Review

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Ontology, as a standard (World Wide Web Consortium recommendation) for representing knowledge in the Semantic Web, has become a fundamental and critical component for developing applications in different real-world scenarios. However, it is widely pointed out that classical ontology model is not sufficient to deal with imprecise and vague knowledge strongly characterizing some real-world applications. Thus, a requirement of extending ontologies naturally arises in many practical applications of knowledge-based systems, in particular the Semantic Web. In order to provide the necessary means to handle such vague and imprecise information there are today many proposals for fuzzy extensions to ontologies, and until now the literature on fuzzy ontologies has been flourishing. To investigate fuzzy ontologies and more importantly serve as helping readers grasp the main ideas and results of fuzzy ontologies, and to highlight an ongoing research on fuzzy approaches for knowledge semantic representation based on ontologies, as well as their applications on various domains, in this paper, we provide a comprehensive overview of fuzzy ontologies. In detail, we first introduce fuzzy ontologies from the most common aspects such as representation (including categories, formal definitions, representation languages, and tools of fuzzy ontologies), reasoning (including reasoning techniques and reasoners), and applications (the most relevant applications about fuzzy ontologies). Then, the other important issues on fuzzy ontologies, such as construction, mapping, integration, query, storage, evaluation, extension, and directions for future research, are also discussed in detail. Also, we make some comparisons and analyses in our whole review.ontology definition languages, such as RDF(S), SHOE, OIL, DAML, DAML + OIL, and web ontology language (OWL), have been developed over the past years (Horrocks et al., 2003). The OWL (Smith et al., 2004) and its successor OWL 2 (Cuenca Grau et al., 2008) is the W3C recommended ontology representation language. The theoretical underpinnings of OWL and ontologies are strongly based on Description Logics (DLs), a subset of first-order logic especially suitable for representing structured knowledge (Horrocks & Sattler, 2001;Baader et al., 2003;Horrocks et al., 2003).Although ontology is a quite expressive formalism, it features limitations, mainly with what can be said about fuzzy information. Nowadays, in ontology-based and many applications information is often vague and imprecise. This is a well-known problem especially for semantics-based applications of the Semantic Web, such as knowledge management, e-commerce, and web portals. For example, a task like a 'doctor appointment' could look like: 'Make me an appointment with a doctor close to my home not too early and of good references' (Stoilos et al., 2010). The conceptual formalism supported by typical ontology may not be sufficient to represent such information and knowledge. Therefore, many proposals have attempted to apply different formalisms...

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Section: Reasoning Of Fuzzy Ontologiesmentioning

confidence: 99%

Section: Reasoning On Fuzzy Description Logics and Fuzzy Ontologiesmentioning

confidence: 99%

“…Also, how to represent and reason on fuzzy UML models with the fuzzy DL was presented by Ma et al . (2011b). Moreover, Zhang et al .…”

Section: Applications and Other Issues Of Fuzzy Ontologiesmentioning

confidence: 99%

Section: Reasoning Of Fuzzy Ontologiesmentioning

confidence: 99%

Section: Reasoning On Fuzzy Description Logics and Fuzzy Ontologiesmentioning

confidence: 99%

See 3 more Smart Citations

A survey on fuzzy ontologies for the Semantic Web

Zhang¹,

Cheng²,

Ma³

2016

The Knowledge Engineering Review

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Non-distributive Description Logic

van der Berg,

De Domenico,

Greco

et al. 2023

Lecture Notes in Computer Science

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We define LE-$$\mathcal {ALC}$$, a generalization of the description logic $$\mathcal {ALC}$$ based on the propositional logic of general (i.e. not necessarily distributive) lattices, and semantically interpreted on relational structures based on formal contexts from Formal Concept Analysis (FCA). The description logic LE-$$\mathcal {ALC}$$ allows us to formally describe databases with objects, features, and formal concepts, represented according to FCA as Galois-stable sets of objects and features. We describe ABoxes and TBoxes in LE-$$\mathcal {ALC}$$, provide a tableaux algorithm for checking the consistency of LE-$$\mathcal {ALC}$$ knowledge bases with acyclic TBoxes, and show its termination, soundness and completeness. Interestingly, consistency checking for LE-$$\mathcal {ALC}$$ with acyclic TBoxes is in PTIME, while the complexity of the consistency checking of classical $$\mathcal {ALC}$$ with acyclic TBoxes is PSPACE-complete.

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