nach oben

Erschienen in:

2016 | OriginalPaper | Buchkapitel

\(\pi \)-SROIQ(D): Possibilistic Description Logic for Uncertain Geographic Information

verfasst von : Safia Bal-Bourai, Aicha Mokhtari

Erschienen in: Trends in Applied Knowledge-Based Systems and Data Science

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

The central question addressed in this paper is to determine how to represent uncertain knowledges present in many applications in geographic domain. The resulting proposition is a possibilistic extension of the very expressive Description Logic \(\mathcal {SROIQ(D)}\), the underlying logic of the OWL2, called \(\pi \)-\(\mathcal {SROIQ(D)}\). It is a solution for handling uncertainty and for dealing with inconsistency in geographic applications. Both syntax and semantics of the proposed description logic are considered. In addition we provide a tableau algorithm for reasoning with the possibilistic DL \(\pi \)-\(\mathcal {SROIQ(D)}\).

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Vorheriges Kapitel How the Strategy Continuity Influences the Evolution of Cooperation in Spatial Prisoner’s Dilemma Game with Interaction Stochasticity

Nächstes Kapitel Smart Solution of Alternative Energy Source for Smart Houses

S used for ALC extended with transitive roles (R+), R for limited complex role inclusion axioms, role disjointness, O for nominals, I for inverse roles, Q for qualified number restrictions and (D) for data values or data types.

A \(\pi \)TBox consists of a finite set of possibilistic GCIs (General Concept Inclusions) and a finite set of possibilistic role axioms RIAs (Role Inclusion Axioms). A \(\pi \)ABox is a finite set of possibilsitic concepts and role assertions axioms expressed in the following forms: (C(a), \(\alpha )\), (R(a, b), \( \alpha )\) or \((\lnot R(a,b)\), \(\alpha )\), T((a, v), \(\alpha )\) or \(\lnot T((a,v)\), \(\alpha )\).

Blocked Node: A node x is blocked iff it is not a root node and it is either directly or indirectly blocked or if there is an ancestor z of x such that z is blocked. If a node x is blocked and none of its ancestors is blocked, then we say that x is directly blocked.

Merging a node y into a node x, means that we add L(y) to L(x), all edges leading to y so that they lead to x and add all the edges leading from y to nominal nodes (contain a nominal) so that they lead from x to the same nominal nodes; then if y is not a root node we remove y (and blockable sub-trees below y) from the completion-graph, otherwise we set L(y) to the empty set and assert that x = y.

Bourai, S.B., Mokhtari, A., Khellaf, F.: Poss–SROIQ(D): possibilistic description logic extension toward an uncertain geographic ontology. In: Catania, B., Cerquitelli, T., Chiusano, S., Guerrini, G., Kämpf, M., Kemper, A., Novikov, B., Palpanas, T., Pokorny, J., Vakali, A. (eds.) New Trends in Databases and Information Systems. AISC, vol. 241, pp. 277–286. Springer, Heidelberg (2014)CrossRef

Bourai, S., R202015: Une logique de description possibiliste pour des connaissances géographiques: application au domaine touristique. Rapport interne, RIIMA, Computer Science Department, USTHB

Benferhat, S., Bouraoui, Z.: Possibilistic DL-Lite. In: Liu, W., Subrahmanian, V.S., Wijsen, J. (eds.) SUM 2013. LNCS, vol. 8078, pp. 346–359. Springer, Heidelberg (2013)CrossRef

Bobillo, F., Straccia, U.: Reasoning with the finitely many-valued Lukasiewicz fuzzy Description Logic SROIQ. Inf. Sci. 181, 758–778 (2011)CrossRefMATH

Bobillo, F., Straccia, U.: Fuzzy ontology representation using OWL 2. Int. J. Approximate Reasoning 52, 1073–1094 (2011)MathSciNetCrossRef

Couchariere, O., Lesot, M.-J., Bouchon-Meunier, B.: Consistency checking for extended description logics. In: Proceedings of the 21st International Workshop on Description Logics, DL 2008. Description Logics, vol. 9, pp. 602–607. CEURWS.org/CEUR Workshop Proceedings (2008)

Dubois, D., Lang, J., Prade, H.: Possibilistic logic. In: Gabbay, D.M., Hogger, C.J., Robinson, J.A., Siekmann, J.H. (eds.) Handbook of Logic in Artificial Intelligence and Logic Programming, pp. 439–513. Oxford University Press, Oxford (1994)

Dubois, D., Mengin, J., Prade, H.: Possibilistic uncertainty and fuzzy features in description logic: a preliminary discussion. In: Sanchez, E. (ed.) Capturing Intelligence: Fuzzy Logic and the Semantic Web, pp. 101–113. Elsevier, Amsterdam (2006)CrossRef

de Saint-Cyr, F.D., Prade, H.: Logical handling of uncertain, ontology-based, spatial information. Fuzzy Sets Syst. (Science Direct) 159, 1515–1534 (2008)MathSciNetCrossRefMATH

10.

Heinsohn, J.: Probabilistic description logics. In: Proceedings UAI 1994, pp. 311–318. Morgan Kaufmann (1994)

11.

Li, J., Simon, W., Huang, G.: Handling temporal uncertainty in GIS domain: a fuzzy approach. In: Symposium on Geospatial Theory, Ottawa (2002)

12.

Horrocks, I., Sattler, U.: Ontology reasoning in the SHOQ(D) description logic. In: Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence (2001)

13.

Horrocks, I., Kutz, O., Sattler, U.: The even more irresistible SROIQ. In: Doherty, P., Mylopoulos, J., Welty, C.A. (eds.) Proceedings of the 10th International Conference of Knowledge Representation and Reasoning (KR 2006), Lake District, UK (2006)

14.

Jaeger, M.: Probabilistic role models and the guarded fragment. In: Proceedings IPMU 2004, pp. 235–242 (2004). Extended version in Int. J. Uncertain. Fuzz. Knowl.-Based Syst. 14(1), 43–60 (2006)

15.

Krotzsch, M., et al.: OWL 2 web ontology language primer. Technical report, W3C October (2009)

16.

Liau, C.-J., Yao, Y.Y.: Information retrieval by possibilistic reasoning. In: Mayr, H.C., Lazanský, J., Quirchmayr, G., Vogel, P. (eds.) DEXA 2001. LNCS, vol. 2113, pp. 52–61. Springer, Heidelberg (2001)CrossRef

17.

Lukasiewicz, T.: Expressive probabilistic description logics. Artif. Intell. 172(67), 852–883 (2008)MathSciNetCrossRefMATH

18.

Pfoser, D., Tryfona, N., Jensen, C.S.: Indeterminacy and spatiotemporal data: basic definitions and case study. GeoInformatica 9(3), 211–236 (2005)CrossRef

19.

Qi, G., Pan, J., Ji, Q.: Possibilistic description logics extension. In: Proceedings of the International Workshop on Description Logics (DL 2007), pp. 435–442 (2007)

20.

Qi, G., Ji, Q., Pan, J.Z., Du, J.: PossDL — a possibilistic DL reasoner for uncertainty reasoning and inconsistency handling. In: Aroyo, L., Antoniou, G., Hyvönen, E., Teije, A., Stuckenschmidt, H., Cabral, L., Tudorache, T. (eds.) ESWC 2010, Part II. LNCS, vol. 6089, pp. 416–420. Springer, Heidelberg (2010)CrossRef

21.

Schneider, M.: Uncertainty management for spatial data in databases: fuzzy spatial data types. In: Güting, R.H., Papadias, D., Lochovsky, F.H. (eds.) SSD 1999. LNCS, vol. 1651, pp. 330–351. Springer, Heidelberg (1999)CrossRef

22.

Giorgos, G., Stamou, G.: Reasoning with Fuzzy Extensions of OWL and OWL 2 (2013)

23.

Shu, H., Spaccapietra, S., Parent, C., Sedas, D.Q.: Uncertainty of geographic information and its support in MADS. In: ISSDQ03 Proceedings (2003)

24.

Straccia, U.: Reasoning within fuzzy description logics. J. Artif. Intell. Res. 14, 137–166 (2001)MathSciNetMATH

25.

Zadeh, L.A.: Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets Syst. 1(1), 3–28 (1978)MathSciNetCrossRefMATH

Titel: -SROIQ(D): Possibilistic Description Logic for Uncertain Geographic Information
verfasst von: Safia Bal-Bourai
Aicha Mokhtari
Verlag: Springer International Publishing
Buch: Trends in Applied Knowledge-Based Systems and Data Science
Print ISBN: 978-3-319-42006-6

Electronic ISBN: 978-3-319-42007-3

Copyright-Jahr: 2016
DOI: https://doi.org/10.1007/978-3-319-42007-3_69

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"