Semantic Reasoning with Uncertain Information from Unreliable Sources

  • Murat ŞensoyEmail author
  • Lance Kaplan
  • Geeth de Mel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9862)


Intelligent software agents may significantly benefit from semantic reasoning. However, existing semantic reasoners are based on Description Logics, which cannot handle vague, incomplete, and unreliable knowledge. In this paper, we propose \(\mathcal {S}\textsf {DL}\text {-}\textsf {Lite}\) which extends \(\textsf {DL}\text {-}\textsf {Lite}_{{R}}\) with subjective opinions to represent uncertainty in knowledge. We directly incorporate trust into the reasoning so that the inconsistencies in the knowledge can be resolved based on trust evidence analysis. Therefore, the proposed logic can handle uncertain information from unreliable sources. We demonstrate how \(\mathcal {S}\textsf {DL}\text {-}\textsf {Lite}\) can be used for semantic fusion of uncertain information from unreliable sources and show that \(\mathcal {S}\textsf {DL}\text {-}\textsf {Lite}\) reasoner can estimate the ground truth with a minimal error.


  1. 1.
    Artz, D., Gil, Y.: A survey of trust in computer science and the Semantic Web. Web Semant.: Sci. Serv. Agents World Wide Web 5(2), 58–71 (2007)CrossRefGoogle Scholar
  2. 2.
    Baader, F., McGuiness, D.L., Nardi, D., Patel-Schneider, P.: Description Logic Handbook: Theory, Implementation and Applications. Cambridge University Press, Cambridge (2002)Google Scholar
  3. 3.
    Boyd, S., Vandenberghe, L.: Convex Optimization. Cambridge University Press, New York (2004)CrossRefzbMATHGoogle Scholar
  4. 4.
    Calvanese, D., Giacomo, G., Lembo, D., Lenzerini, M., Rosati, R.: Tractable reasoning and efficient query answering in description logics: the DL-lite family. J. Autom. Reason. 39(3), 385–429 (2007)MathSciNetCrossRefzbMATHGoogle Scholar
  5. 5.
    Golbeck, J., Halaschek-Wiener, C.: Trust-based revision for expressive web syndication. J. Logic Comput. 19(5), 771–790 (2009)MathSciNetCrossRefzbMATHGoogle Scholar
  6. 6.
    Gómez, S.A.: Reasoning with inconsistent possibilistic description logics ontologies with disjunctive assertions. J. Comput. Sci. Technol. 15 (2015)Google Scholar
  7. 7.
    Jøsang, A.: Subjective Logic. Springer, Heidelberg (2016)CrossRefzbMATHGoogle Scholar
  8. 8.
    Jøsang, A., Ismail, R.: The beta reputation system. In: Proceedings of the 15th Bled Electronic Commerce Conference e-Reality: Constructing the e-Economy, pp. 48–64 (2002)Google Scholar
  9. 9.
    Qi, G., Pan, J.Z., Ji, Q.: Extending description logics with uncertainty reasoning in possibilistic logic. In: Mellouli, K. (ed.) ECSQARU 2007. LNCS (LNAI), vol. 4724, pp. 828–839. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  10. 10.
    Sensoy, M., Fokoue, A., Pan, J.Z., Norman, T.J.: Reasoning about uncertain information and conflict resolution through trust revision. In: Proceedings of 12th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 837–844 (2013)Google Scholar
  11. 11.
    Shafer, G.: A Mathematical Theory of Evidence. Princeton University Press, Princeton (1976)zbMATHGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Department of Computer ScienceOzyegin UniversityIstanbulTurkey
  2. 2.US Army Research LabAdelphiUSA
  3. 3.IBM T. J. Watson Research CenterHawthorneUSA

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